Variations on a theme: Polycomb group proteins in plants

Polycomb group (PcG) proteins evolved early in evolution, probably in the common ancestor of animals and plants. In some unicellular organisms, such as Chlamydomonas and Tetrahymena, PcG proteins silence genes in heterochromatin, suggesting an ancestral function in genome defence. In angiosperms, the PcG system controls many developmental transitions. A PcG function in the vernalization response evolved especially in Brassicaceaea. Thus, the role of PcG proteins has changed during evolution to match novel needs. Recent studies identified many proteins associated with plant PcG protein complexes. Possible functions of these interactions are discussed here. We highlight recent findings about recruitment of PcG proteins in plants in comparison with animal system. Through the new data, a picture emerges in which PcG protein complexes do not function in sequential linear pathways but as dynamically interacting networks allowing stabilizing feedback loops. We discuss how the interplay between different PcG protein complexes can enable establishment, maintenance, and epigenetic inheritance of H3K27me

FLC or not FLC: the other side of vernalization

Vernalization is the promotion of the competence for flowering by long periods of low temperatures such as those typically experienced during winters. In Arabidopsis, the vernalization response is, to a large extent, mediated by the repression of the floral repressor FLC, and the stable epigenetic silencing of FLC after cold treatments is essential for vernalization. In addition to FLC, other vernalization targets exist in Arabidopsis. In grasses, vernalization seems to be entirely independent of FLC. Here, the current understanding of FLC-independent branches of the vernalization pathway in Arabidopsis and vernalization without FLC in grasses is discussed. This review focuses on the role of AGL19, AGL24, and the MAF genes in Arabidopsis. Interestingly, vernalization acts through related molecular machineries on distinct targets. In particular, protein complexes similar to Drosophila Polycomb Repressive Complex 2 play a prominent role in establishing an epigenetic cellular memory for cold-regulated expression states of AGL19 and FLC. Finally, the similar network topology of the apparently independently evolved vernalization pathways of grasses and Arabidopsis is discusse

Control of trichome branching by Chromatin Assembly Factor-1

<p>Abstract</p> <p>Background</p> <p>Chromatin dynamics and stability are both required to control normal development of multicellular organisms. Chromatin assembly factor CAF-1 is a histone chaperone that facilitates chromatin formation and the maintenance of specific chromatin states. In plants and animals CAF-1 is essential for normal development, but it is poorly understood which developmental pathways require CAF-1 function.</p> <p>Results</p> <p>Mutations in all three CAF-1 subunits affect Arabidopsis trichome morphology and lack of CAF-1 function results in formation of trichomes with supernumerary branches. This phenotype can be partially alleviated by external sucrose. In contrast, other aspects of the CAF-1 mutant phenotype, such as defective meristem function and organ formation, are aggravated by external sucrose. Double mutant analyses revealed epistatic interactions between CAF-1 mutants and <it>stichel</it>, but non-epistatic interactions between CAF-1 mutants and <it>glabra3 </it>and <it>kaktus</it>. In addition, mutations in CAF-1 could partly suppress the strong overbranching and polyploidization phenotype of <it>kaktus </it>mutants.</p> <p>Conclusion</p> <p>CAF-1 is required for cell differentiation and regulates trichome development together with STICHEL in an endoreduplication-independent pathway. This function of CAF-1 can be partially substituted by application of exogenous sucrose. Finally, CAF-1 is also needed for the high degree of endoreduplication in <it>kaktus </it>mutants and thus for the realization of <it>kaktus</it>' extreme overbranching phenotype.</p

Arabidopsis transcript profiling on Affymetrix GeneChip arrays

DNA microarrays are becoming a frequently used research tool. Whilst several studies have confirmed the reproducibility of analysing the same RNA samples on duplicate arrays, there is little analysis of the reproducibility of the results of transcript profiling between microarrays carrying different probes to a common set of genes. To address this question, we compared the performance and reproducibility of two microarrays commonly used in plant research, the Affymetrix Arabidopsis AG array containing more than 8000 probe sets and the Affymetrix Arabidopsis ATH1 array containing more than 22 000 redesigned probe sets. A total of 21 different RNA samples were labelled and hybridized in parallel to the two microarray types. Focusing on the overlap of more than 7300 targets detected with both arrays, we found a high degree of reproducibility. Despite the use of different probe sets, both signal and signal log ratio were very similar for most genes. However, genes that were called absent or not changed by Affymetrix' statistical algorithm implemented in MAS5.0 showed considerably less conservation of expression patterns. Moreover, we identified about 300 genes that yielded strongly different measurements with the two microarrays, emphasizing that RNA profiling data need careful interpretation. Overall, this study shows that results obtained with ATH1 and AG arrays are very comparable and hence that the analysis is largely independent of probe sets. However, the result emphasize the need for appropriate filtering schemes such as those based on the present and change calls provided by MAS5.0 rather than reliance solely on signal value

Causal Stability Ranking

Genotypic causes of a phenotypic trait are typically determined via randomized controlled intervention experiments. Such experiments are often prohibitive with respect to durations and costs. We therefore consider inferring stable rankings of genes, according to their causal effects on a phenotype, from observational data only. Our method allows for efficient design and prioritization of future experiments, and due to its generality it is useable for a broad spectrum of applications

Global transcript profiling of transgenic plants constitutively overexpressing the RNA-binding protein AtGRP7

Streitner C, Hennig L, Korneli C, Staiger D. Global transcript profiling of transgenic plants constitutively overexpressing the RNA-binding protein AtGRP7. BMC Plant Biology. 2010;10(1): 221.Background: The clock-controlled RNA-binding protein AtGRP7 influences circadian oscillations of its own transcript at the post-transcriptional level. To identify additional targets that are regulated by AtGRP7, transcript profiles of transgenic plants constitutively overexpressing AtGRP7 (AtGRP7-ox) and wild type plants were compared. Results: Approximately 1.4% of the transcripts represented on the Affymetrix ATH1 microarray showed changes in steady-state abundance upon AtGRP7 overexpression. One third of the differentially expressed genes are controlled by the circadian clock, and they show a distinct bias of their phase: The up-regulated genes preferentially peak around dawn, roughly opposite to the AtGRP7 peak abundance whereas the down-regulated genes preferentially peak at the end of the day. Further, transcripts responsive to abiotic and biotic stimuli were enriched among AtGRP7 targets. Transcripts encoding the pathogenesis-related PR1 and PR2 proteins were elevated in AtGRP7-ox plants but not in plants overexpressing AtGRP7 with a point mutation in the RNA-binding domain, indicating that the regulation involves RNA binding activity of AtGRP7. Gene set enrichment analysis uncovered components involved in ribosome function and RNA metabolism among groups of genes upregulated in AtGRP7-ox plants, consistent with its role in post-transcriptional regulation. Conclusion: Apart from regulating a suite of circadian transcripts in a time-of-day dependent manner AtGRP7, both directly and indirectly, affects other transcripts including transcripts responsive to abiotic and biotic stimuli. This suggests a regulatory role of AtGRP7 in the output of the endogenous clock and a complex network of transcripts responsive to external stimuli downstream of the AtGRP7 autoregulatory circuit

PlantDB – a versatile database for managing plant research

Background Research in plant science laboratories often involves usage of many different species, cultivars, ecotypes, mutants, alleles or transgenic lines. This creates a great challenge to keep track of the identity of experimental plants and stored samples or seeds. Results Here, we describe PlantDB – a Microsoft® Office Access database – with a user-friendly front-end for managing information relevant for experimental plants. PlantDB can hold information about plants of different species, cultivars or genetic composition. Introduction of a concise identifier system allows easy generation of pedigree trees. In addition, all information about any experimental plant – from growth conditions and dates over extracted samples such as RNA to files containing images of the plants – can be linked unequivocally. Conclusion We have been using PlantDB for several years in our laboratory and found that it greatly facilitates access to relevant information.ISSN:1746-481

H2A ubiquitination is essential for Polycomb Repressive Complex 1-mediated gene regulation in Marchantia polymorpha

Background Polycomb repressive complex 1 (PRC1) and PRC2 are chromatin regulators maintaining transcriptional repression. The deposition of H3 lysine 27 tri-methylation (H3K27me3) by PRC2 is known to be required for transcriptional repression, whereas the contribution of H2A ubiquitination (H2Aub) in the Polycomb repressive system remains unclear in plants. Results We directly test the requirement of H2Aub for gene regulation in Marchantia polymorpha by generating point mutations in H2A that prevent ubiquitination by PRC1. These mutants show reduced H3K27me3 levels on the same target sites as mutants defective in PRC1 subunits MpBMI1 and the homolog MpBMI1L, revealing that PRC1-catalyzed H2Aub is essential for Polycomb system function. Furthermore, by comparing transcriptome data between mutants in MpH2A and MpBMI1/1L, we demonstrate that H2Aub contributes to the PRC1-mediated transcriptional level of genes and transposable elements. Conclusion Together, our data demonstrates that H2Aub plays a direct role in H3K27me3 deposition and is required for PRC1-mediated transcriptional changes in both genes and transposable elements in Marchantia

Causal stability ranking

Genotypic causes of a phenotypic trait are typically determined via randomized controlled intervention experiments. Such experiments are often prohibitive with respect to durations and costs, and informative prioritization of experiments is desirable. We therefore consider predicting stable rankings of genes (covariates), according to their total causal effects on a phenotype (response), from observational data. Since causal effects are generally non-identifiable from observational data only, we use a method that can infer lower bounds for the total causal effect under some assumptions. We validated our method, which we call Causal Stability Ranking (CStaR), in two situations. First, we performed knock-out experiments with Arabidopsis thaliana according to a predicted ranking based on observational gene expression data, using flowering time as phenotype of interest. Besides several known regulators of flowering time, we found almost half of the tested top ranking mutants to have a significantly changed flowering time. Second, we compared CStaR to established regression-based methods on a gene expression dataset of Saccharomyces cerevisiae. We found that CStaR outperforms these established methods. Our method allows for efficient design and prioritization of future intervention experiments, and due to its generality it can be used for a broad spectrum of applications. Availability: The full table of ranked genes, all raw data and an example R script for CStaR are available from the Bioinformatics website. Contact: [email protected] Supplementary Information: Supplementary data are available at Bioinformatics onlin