Studien zur pflanzenspezifischen WRKY-Transkriptionsfaktorfamilie - Vergleichende Analyse zwischen dem Moos, Physcomitrella patens, und höheren Pflanzen sowie eine gesamtgenomische Betrachtung von WRKY-DNA-Bindungsstellen

Die Mitglieder der Multigenfamilie der pflanzenspezifischen WRKY-Transkriptionsfaktoren sind zwischen den höheren Pflanzen und der niederen Pflanze Physcomitrella patens hoch konserviert. Heterolog exprimiertes PpWRKY20 ist im Nucleus lokalisiert. Sowohl für PpWRKY20 als auch für AtWRKY11, ein Homolog zu PpWKY20 aus Arabidopsis thaliana, konnte Transaktivierung in Hefe festgestellt werden. Während AtWRKY11 in vitro zu W-Box-Elementen bindet, konnte PpWRKY20 dies nicht. Außerdem konnte PpWRKY20 auch keine Reportergenaktivität über W-Box in vivo induzieren. Biolistischer Partikelbeschuss wurde etabliert, um Protonema mit Promotor-Reportergenkonstrukten zu transformieren. Eine dosisabhängige GUS-Aktivität konnte nach dem Beschuss mit einem 4xW2-Box-Konstrukt und nach sprühen mit flg22-Elizitor gefunden werden. Expressionsanalysenzeigten, dass einige der bekannten PpWRKY-Gene ebenfalls induziert wurden. Nach Behandlung mit nicht-funktionellem Elizitor oder mit BSA wurde herausgefunden, dass die WRKY-Gene generell durch Peptide induziert wurden. Eine phylogenetische Analyse mit den Sequenzen für die WRKY-Domänen aus P. patens, A. thaliana und Oryza sativa. So konnten die paralogen und orthologen WRKY-Gene aus A. thliana und O. sativa gefunden werden. Zusätzlich könnten die WRKY-Gene der Gruppe I und Gruppe IId die phylogenetisch ältesten sein. Funktionelle und strukturelle Analysen von orthologen WRKY-Genen höherer Pflanzen zeigten hohe Ähnlichkeiten. In diesem Zusammenhang erscheint es sinnvoll auch W-box-Elemente zu untersuchen. Das neu entwickelten MotifMapper-Programm wurde verwendet die Promotor-Architektur von fünf Modellorganismen zu untersuchen. Mit MotifMapper konnten neue cis-Elemente in Pflanzen gefunden werden. Die Frequenz und die Verteilung von pathogenresponsiven Elementen wurde gesamtgenomisch in A. thaliana untersucht. Dabei kamen die W-Boxen und die G-Boxen als combinierte funktionelle Einheiten vor. Mit einem Motiv aus sich wiederholenden W-Boxen wurden ähnliche Motive in Promotoren koregulierter Gene gefunden

Phylogenetic Analyses and GAGA-Motif Binding Studies of BBR/BPC Proteins Lend to Clues in GAGA-Motif Recognition and a Regulatory Role in Brassinosteroid Signaling

Plant GAGA-motif binding factors are encoded by the BARLEY B RECOMBINANT / BASIC PENTACYSTEINE (BBR/BPC) family, which fulfill indispensable functions in growth and development. BBR/BPC proteins control flower development, size of the stem cell niche and seed development through transcriptional regulation of homeotic transcription factor genes. They are responsible for the context dependent recruitment of Polycomb repressive complexes (PRC) or other repressive proteins to GAGA-motifs, which are contained in Polycomb repressive DNA-elements (PREs). Hallmark of the protein family is the highly conserved BPC domain, which is required for DNA binding. Here we study the evolution and diversification of the BBR/BPC family and its DNA-binding domain. Our analyses supports a further division of the family into four main groups (I–IV) and several subgroups, to resolve a strict monophyletic descent of the BPC domain. We prove a polyphyletic origin for group III proteins, which evolved from group I and II members through extensive loss of domains in the N-terminus. Conserved motif searches lend to the identification of a WAR/KHGTN consensus and a TIR/K motif at the very C-terminus of the BPC-domain. We could show by DPI-ELISA that this signature is required for DNA-binding in AtBPC1. Additional binding studies with AtBPC1, AtBPC6 and mutated oligonucleotides consolidated the binding to GAGA tetramers. To validate these findings, we used previously published ChIP-seq data from GFP-BPC6. We uncovered that many genes of the brassinosteroid signaling pathway are targeted by AtBPC6. Consistently, bpc6, bpc4 bpc6, and lhp1 bpc4 bpc4 mutants display brassinosteroid-dependent root growth phenotypes. Both, a function in brassinosteroid signaling and our phylogenetic data supports a link between BBR/BPC diversification in the land plant lineage and the complexity of flower and seed plant evolution

EDISA: extracting biclusters from multiple time-series of gene expression profiles

<p>Abstract</p> <p>Background</p> <p>Cells dynamically adapt their gene expression patterns in response to various stimuli. This response is orchestrated into a number of gene expression modules consisting of co-regulated genes. A growing pool of publicly available microarray datasets allows the identification of modules by monitoring expression changes over time. These time-series datasets can be searched for gene expression modules by one of the many clustering methods published to date. For an integrative analysis, several time-series datasets can be joined into a three-dimensional <it>gene-condition-time </it>dataset, to which standard clustering or biclustering methods are, however, not applicable. We thus devise a probabilistic clustering algorithm for <it>gene-condition-time </it>datasets.</p> <p>Results</p> <p>In this work, we present the EDISA (Extended Dimension Iterative Signature Algorithm), a novel probabilistic clustering approach for 3D <it>gene-condition-time </it>datasets. Based on mathematical definitions of gene expression modules, the EDISA samples initial modules from the dataset which are then refined by removing genes and conditions until they comply with the module definition. A subsequent extension step ensures gene and condition maximality. We applied the algorithm to a synthetic dataset and were able to successfully recover the implanted modules over a range of background noise intensities. Analysis of microarray datasets has lead us to define three biologically relevant module types: 1) We found modules with independent response profiles to be the most prevalent ones. These modules comprise genes which are co-regulated under several conditions, yet with a different response pattern under each condition. 2) Coherent modules with similar responses under all conditions occurred frequently, too, and were often contained within these modules. 3) A third module type, which covers a response specific to a single condition was also detected, but rarely. All of these modules are essentially different types of biclusters.</p> <p>Conclusion</p> <p>We successfully applied the EDISA to different 3D datasets. While previous studies were mostly aimed at detecting coherent modules only, our results show that coherent responses are often part of a more general module type with independent response profiles under different conditions. Our approach thus allows for a more comprehensive view of the gene expression response. After subsequent analysis of the resulting modules, the EDISA helped to shed light on the global organization of transcriptional control. An implementation of the algorithm is available at http://www-ra.informatik.uni-tuebingen.de/software/IAGEN/.</p

DPI-ELISA: a fast and versatile method to specify the binding of plant transcription factors to DNA in vitro

<p>Abstract</p> <p>Background</p> <p>About 10% of all genes in eukaryote genomes are predicted to encode transcription factors. The specific binding of transcription factors to short DNA-motifs influences the expression of neighbouring genes. However, little is known about the DNA-protein interaction itself. To date there are only a few suitable methods to characterise DNA-protein-interactions, among which the EMSA is the method most frequently used in laboratories. Besides EMSA, several protocols describe the effective use of an ELISA-based transcription factor binding assay e.g. for the analysis of human NFκB binding to specific DNA sequences.</p> <p>Results</p> <p>We provide a unified protocol for this type of ELISA analysis, termed DNA-Protein-Interaction (DPI)-ELISA. Qualitative analyses with His-epitope tagged plant transcription factors expressed in <it>E. coli </it>revealed that EMSA and DPI-ELISA result in comparable and reproducible data. The binding of <it>At</it>bZIP63 to the C-box and <it>At</it>WRKY11 to the W2-box could be reproduced and validated by both methods. We next examined the physical binding of the C-terminal DNA-binding domains of <it>At</it>WRKY33, <it>At</it>WRKY50 and <it>At</it>WRKY75 to the W2-box. Although the DNA-binding domain is highly conserved among the WRKY proteins tested, the use of the DPI-ELISA discloses differences in W2-box binding properties between these proteins. In addition to these well-studied transcription factor families, we applied our protocol to <it>At</it>BPC2, a member of the so far uncharacterised plant specific Basic Pentacysteine transcription factor family. We could demonstrate binding to GA/TC-dinucleotide repeat motifs by our DPI-ELISA protocol. Different buffers and reaction conditions were examined.</p> <p>Conclusions</p> <p>We successfully applied our DPI-ELISA protocol to investigate the DNA-binding specificities of three different classes of transcription factors from <it>Arabidopsis thaliana</it>. However, the analysis of the binding affinity of any DNA-binding protein to any given DNA sequence can be performed <it>via </it>this method. The DPI-ELISA is cost efficient, less time-consuming than other methods and provides a qualitative and quantitative readout. The presented DPI-ELISA protocol is accompanied by advice on trouble-shooting, which will enable scientists to rapidly establish this versatile and easy to use method in their laboratories.</p

Phylogenetic and comparative gene expression analysis of barley (Hordeum vulgare) WRKY transcription factor family reveals putatively retained functions between monocots and dicots

WRKY proteins belong to the WRKY-GCM1 superfamily of zinc finger transcription factors that have been subject to a large plant-specific diversification. For the cereal crop barley (Hordeum vulgare), three different WRKY proteins have been characterized so far, as regulators in sucrose signaling, in pathogen defense, and in response to cold and drought, respectively. However, their phylogenetic relationship remained unresolved. In this study, we used the available sequence information to identify a minimum number of 45 barley WRKY transcription factor (HvWRKY) genes. According to their structural features the HvWRKY factors were classified into the previously defined polyphyletic WRKY subgroups 1 to 3. Furthermore, we could assign putative orthologs of the HvWRKY proteins in Arabidopsis and rice. While in most cases clades of orthologous proteins were formed within each group or subgroup, other clades were composed of paralogous proteins for the grasses and Arabidopsis only, which is indicative of specific gene radiation events. To gain insight into their putative functions, we examined expression profiles of WRKY genes from publicly available microarray data resources and found group specific expression patterns. While putative orthologs of the HvWRKY transcription factors have been inferred from phylogenetic sequence analysis, we performed a comparative expression analysis of WRKY genes in Arabidopsis and barley. Indeed, highly correlative expression profiles were found between some of the putative orthologs. HvWRKY genes have not only undergone radiation in monocot or dicot species, but exhibit evolutionary traits specific to grasses. HvWRKY proteins exhibited not only sequence similarities between orthologs with Arabidopsis, but also relatedness in their expression patterns. This correlative expression is indicative for a putative conserved function of related WRKY proteins in mono- and dicot species

Identification of the sex-determining factor in the liverwort Marchantia polymorpha reveals unique evolution of sex chromosomes in a haploid system

半数体生物の性染色体上の性決定遺伝子を解明 --コケがもつ現生生物最古の起源の性染色体--. 京都大学プレスリリース. 2021-11-08.Sex determination is a central process for sexual reproduction and is often regulated by a sex determinant encoded on a sex chromosome. Rules that govern the evolution of sex chromosomes via specialization and degeneration following the evolution of a sex determinant have been well studied in diploid organisms. However, distinct predictions apply to sex chromosomes in organisms where sex is determined in the haploid phase of the life cycle: both sex chromosomes, female U and male V, are expected to maintain their gene functions, even though both are non-recombining. This is in contrast to the X-Y (or Z-W) asymmetry and Y (W) chromosome degeneration in XY (ZW) systems of diploids. Here, we provide evidence that sex chromosomes diverged early during the evolution of haploid liverworts and identify the sex determinant on the Marchantia polymorpha U chromosome. This gene, Feminizer, encodes a member of the plant-specific BASIC PENTACYSTEINE transcription factor family. It triggers female differentiation via regulation of the autosomal sex-determining locus of FEMALE GAMETOPHYTE MYB and SUPPRESSOR OF FEMINIZATION. Phylogenetic analyses of Feminizer and other sex chromosome genes indicate dimorphic sex chromosomes had already been established 430 mya in the ancestral liverwort. Feminizer also plays a role in reproductive induction that is shared with its gametolog on the V chromosome, suggesting an ancestral function, distinct from sex determination, was retained by the gametologs. This implies ancestral functions can be preserved after the acquisition of a sex determination mechanism during the evolution of a dominant haploid sex chromosome system

Alanine Zipper-Like Coiled-Coil Domains Are Necessary for Homotypic Dimerization of Plant GAGA-Factors in the Nucleus and Nucleolus

GAGA-motif binding proteins control transcriptional activation or repression of homeotic genes. Interestingly, there are no sequence similarities between animal and plant proteins. Plant BBR/BPC-proteins can be classified into two distinct groups: Previous studies have elaborated on group I members only and so little is known about group II proteins. Here, we focused on the initial characterization of AtBPC6, a group II protein from Arabidopsis thaliana. Comparison of orthologous BBR/BPC sequences disclosed two conserved signatures besides the DNA binding domain. A first peptide signature is essential and sufficient to target AtBPC6-GFP to the nucleus and nucleolus. A second domain is predicted to form a zipper-like coiled-coil structure. This novel type of domain is similar to Leucine zippers, but contains invariant alanine residues with a heptad spacing of 7 amino acids. By yeast-2-hybrid and BiFC-assays we could show that this Alanine zipper domain is essential for homotypic dimerization of group II proteins in vivo. Interhelical salt bridges and charge-stabilized hydrogen bonds between acidic and basic residues of the two monomers are predicted to form an interaction domain, which does not follow the classical knobs-into-holes zipper model. FRET-FLIM analysis of GFP/RFP-hybrid fusion proteins validates the formation of parallel dimers in planta. Sequence comparison uncovered that this type of domain is not restricted to BBR/BPC proteins, but is found in all kingdoms

Predicting DNA-Binding Specificities of Eukaryotic Transcription Factors

Today, annotated amino acid sequences of more and more transcription factors (TFs) are readily available. Quantitative information about their DNA-binding specificities, however, are hard to obtain. Position frequency matrices (PFMs), the most widely used models to represent binding specificities, are experimentally characterized only for a small fraction of all TFs. Even for some of the most intensively studied eukaryotic organisms (i.e., human, rat and mouse), roughly one-sixth of all proteins with annotated DNA-binding domain have been characterized experimentally. Here, we present a new method based on support vector regression for predicting quantitative DNA-binding specificities of TFs in different eukaryotic species. This approach estimates a quantitative measure for the PFM similarity of two proteins, based on various features derived from their protein sequences. The method is trained and tested on a dataset containing 1 239 TFs with known DNA-binding specificity, and used to predict specific DNA target motifs for 645 TFs with high accuracy