Compact tomato seedlings and plants upon overexpression of a tomato chromatin remodelling ATPase gene.

Control of plant growth is an important aspect of crop productivity and yield in agriculture. Overexpression of the AtCHR12/23 genes in Arabidopsis thaliana reduced growth habit without other morphological changes. These two genes encode Snf2 chromatin remodelling ATPases. Here, we translate this approach to the horticultural crop tomato (Solanum lycopersicum). We identified and cloned the single tomato ortholog of the two Arabidopsis Snf2 genes, designated SlCHR1. Transgenic tomato plants (cv. Micro-Tom) that constitutively overexpress the coding sequence of SlCHR1 show reduced growth in all developmental stages of tomato. This confirms that SlCHR1 combines the functions of both Arabidopsis genes in tomato. Compared to the wild type, the transgenic seedlings of tomato have significantly shorter roots, hypocotyls and reduced cotyledon size. Transgenic plants have a much more compact growth habit with markedly reduced plant height, severely compacted reproductive structures with smaller flowers and smaller fruits. The results indicate that either GMO-based or non-GMO-based approaches to modulate the expression of chromatin remodelling ATPase genes could develop into methods to control plant growth, for example to replace the use of chemical growth retardants. This approach is likely to be applicable and attractive for any crop for which growth habit reduction has added value.

Towards recommendations for metadata and data handling in plant phenotyping.

Recent methodological developments in plant phenotyping, as well as the growing importance of its applications in plant science and breeding, are resulting in a fast accumulation of multidimensional data. There is great potential for expediting both discovery and application if these data are made publicly available for analysis. However, collection and storage of phenotypic observations is not yet sufficiently governed by standards that would ensure interoperability among data providers and precisely link specific phenotypes and associated genomic sequence information. This lack of standards is mainly a result of a large variability of phenotyping protocols, the multitude of phenotypic traits that are measured, and the dependence of these traits on the environment. This paper discusses the current situation of standardization in the area of phenomics, points out the problems and shortages, and presents the areas that would benefit from improvement in this field. In addition, the foundations of the work that could revise the situation are proposed, and practical solutions developed by the authors are introduced.

Reduced seed germination in Arabidopsis over-expressing SWI/SNF2 ATPase genes.

In the life of flowering plants, seed germination is a critical step to ensure survival into the next generation. Generally the seed prior to germination has been in a dormant state with a low rate of metabolism. In the transition from a dormant seed to a germinating seed, various epigenetic mechanisms play a regulatory role. Here, we demonstrate that the over-expression of chromatin remodeling ATPase genes (AtCHR12 or AtCHR23) reduced the frequency of seed germination in Arabidopsis thaliana up to 30% relative to the wild-type seeds. On the other hand, single loss-of-function mutations of the two genes did not affect seed germination. The reduction of germination in over-expressing mutants was more pronounced in stress conditions (salt or high temperature), showing the impact of the environment. Reduced germinations upon over-expression coincided with increased transcript levels of seed maturation genes and with reduced degradation of their mRNAs stored in dry seeds. Our results indicate that repression of AtCHR12/23 gene expression in germinating wild-type Arabidopsis seeds is required for full germination. This establishes a functional link between chromatin modifiers and regulatory networks towards seed maturation and germination.

Prioritization of candidate genes in QTL regions based on associations between traits and biological processes.

BACKGROUND: Elucidation of genotype-to-phenotype relationships is a major challenge in biology. In plants, it is the basis for molecular breeding. Quantitative Trait Locus (QTL) mapping enables to link variation at the trait level to variation at the genomic level. However, QTL regions typically contain tens to hundreds of genes. In order to prioritize such candidate genes, we show that we can identify potentially causal genes for a trait based on overrepresentation of biological processes (gene functions) for the candidate genes in the QTL regions of that trait. RESULTS: The prioritization method was applied to rice QTL data, using gene functions predicted on the basis of sequence- and expression-information. The average reduction of the number of genes was over ten-fold. Comparison with various types of experimental datasets (including QTL fine-mapping and Genome Wide Association Study results) indicated both statistical significance and biological relevance of the obtained connections between genes and traits. A detailed analysis of flowering time QTLs illustrates that genes with completely unknown function are likely to play a role in this important trait. CONCLUSIONS: Our approach can guide further experimentation and validation of causal genes for quantitative traits. This way it capitalizes on QTL data to uncover how individual genes influence trait variation.

Over-expression of Arabidopsis AtCHR23 chromatin remodeling ATPase results in increased variability of growth and gene expression.

BACKGROUND: Plants are sessile organisms that deal with their -sometimes adverse- environment in well-regulated ways. Chromatin remodeling involving SWI/SNF2-type ATPases is thought to be an important epigenetic mechanism for the regulation of gene expression in different developmental programs and for integrating these programs with the response to environmental signals. In this study, we report on the role of chromatin remodeling in Arabidopsis with respect to the variability of growth and gene expression in relationship to environmental conditions. RESULTS: Already modest (2-fold) over-expression of the AtCHR23 ATPase gene in Arabidopsis results in overall reduced growth compared to the wild-type. Detailed analyses show that in the root, the reduction of growth is due to reduced cell elongation. The reduced-growth phenotype requires sufficient light and is magnified by applying deliberate abiotic (salt, osmotic) stress. In contrast, the knockout mutation of AtCHR23 does not lead to such visible phenotypic effects. In addition, we show that over-expression of AtCHR23 increases the variability of growth in populations of genetically identical plants. These data indicate that accurate and controlled expression of AtCHR23 contributes to the stability or robustness of growth. Detailed RNAseq analyses demonstrate that upon AtCHR23 over-expression also the variation of gene expression is increased in a subset of genes that associate with environmental stress. The larger variation of gene expression is confirmed in individual plants with the help of independent qRT-PCR analysis. CONCLUSIONS: Over-expression of AtCHR23 gives Arabidopsis a phenotype that is markedly different from the growth arrest phenotype observed upon over-expression of AtCHR12, the paralog of AtCHR23, in response to abiotic stress. This demonstrates functional sub-specialization of highly similar ATPases in Arabidopsis. Over-expression of AtCHR23 increases the variability of growth among genetically identical individuals in a way that is consistent with increased variability of expression of a distinct subset of genes that associate with environmental stress. We propose that ATCHR23-mediated chromatin remodeling is a potential component of a buffer system in plants that protects against environmentally-induced phenotypic and transcriptional variation.

Genomic analysis of the native European Solanum species, S. dulcamara.

BACKGROUND: Solanum dulcamara (bittersweet, climbing nightshade) is one of the few species of the Solanaceae family native to Europe. As a common weed it is adapted to a wide range of ecological niches and it has long been recognized as one of the alternative hosts for pathogens and pests responsible for many important diseases in potato, such as Phytophthora. At the same time, it may represent an alternative source of resistance genes against these diseases. Despite its unique ecology and potential as a genetic resource, genomic research tools are lacking for S. dulcamara. We have taken advantage of next-generation sequencing to speed up research on and use of this non-model species. RESULTS: In this work, we present the first large-scale characterization of the S. dulcamara transcriptome. Through comparison of RNAseq reads from two different accessions, we were able to predict transcript-based SNP and SSR markers. Using the SNP markers in combination with genomic AFLP and CAPS markers, the first genome-wide genetic linkage map of bittersweet was generated. Based on gene orthology, the markers were anchored to the genome of related Solanum species (tomato, potato and eggplant), revealing both conserved and novel chromosomal rearrangements. This allowed a better estimation of the evolutionary moment of rearrangements in a number of cases and showed that chromosomal breakpoints are regularly re-used. CONCLUSION: Knowledge and tools developed as part of this study pave the way for future genomic research and exploitation of this wild Solanum species. The transcriptome assembly represents a resource for functional analysis of genes underlying interesting biological and agronomical traits and, in the absence of the full genome, provides a reference for RNAseq gene expression profiling aimed at understanding the unique biology of S. dulcamara. Cross-species orthology-based marker selection is shown to be a powerful tool to quickly generate a comparative genetic map, which may speed up gene mapping and contribute to the understanding of genome evolution within the Solanaceae family.

Unexpectedly rapid IS1 transposition into an Arabidopsis chromatin remodeling gene.

Common cloning is often associated with instability of certain classes of DNA. Here we report on IS1 transposition as possible source of such instability. During the cloning of Arabidopsis thaliana gene into commercially available vector maintained in widely used Escherichia coli host the insertion of complete IS1 element into the intron of cloned gene was found. The transposition of the IS1 element was remarkably rapid and is likely to be sequence-specific. The use of E. coli strains that lower the copy number of vector or avoiding the presence of the problematic sequence is a solution to the inadvertent transposition of IS1. The transposition of IS1 is rare but it can occur and might confound functional studies of a plant gene.

In silico miRNA prediction in metazoan genomes: balancing between sensitivity and specificity.

BACKGROUND: MicroRNAs (miRNAs), short approximately 21-nucleotide RNA molecules, play an important role in post-transcriptional regulation of gene expression. The number of known miRNA hairpins registered in the miRBase database is rapidly increasing, but recent reports suggest that many miRNAs with restricted temporal or tissue-specific expression remain undiscovered. Various strategies for in silico miRNA identification have been proposed to facilitate miRNA discovery. Notably support vector machine (SVM) methods have recently gained popularity. However, a drawback of these methods is that they do not provide insight into the biological properties of miRNA sequences. RESULTS: We here propose a new strategy for miRNA hairpin prediction in which the likelihood that a genomic hairpin is a true miRNA hairpin is evaluated based on statistical distributions of observed biological variation of properties (descriptors) of known miRNA hairpins. These distributions are transformed into a single and continuous outcome classifier called the L score. Using a dataset of known miRNA hairpins from the miRBase database and an exhaustive set of genomic hairpins identified in the genome of Caenorhabditis elegans, a subset of 18 most informative descriptors was selected after detailed analysis of correlation among and discriminative power of individual descriptors. We show that the majority of previously identified miRNA hairpins have high L scores, that the method outperforms miRNA prediction by threshold filtering and that it is more transparent than SVM classifiers. CONCLUSION: The L score is applicable as a prediction classifier with high sensitivity for novel miRNA hairpins. The L-score approach can be used to rank and select interesting miRNA hairpin candidates for downstream experimental analysis when coupled to a genome-wide set of in silico-identified hairpins or to facilitate the analysis of large sets of putative miRNA hairpin loci obtained in deep-sequencing efforts of small RNAs. Moreover, the in-depth analyses of miRNA hairpins descriptors preceding and determining the L score outcome could be used as an extension to miRBase entries to help increase the reliability and biological relevance of the miRNA registry.

In plants, highly expressed genes are the least compact.

In both the monocot rice and the dicot Arabidopsis, highly expressed genes have more and longer introns and a larger primary transcript than genes expressed at a low level: higher expressed genes tend to be less compact than lower expressed genes. In animal genomes, it is the other way round. Although the length differences in plant genes are much smaller than in animals, these findings indicate that plant genes are in this respect different from animal genes. Explanations for the relationship between gene configuration and gene expression in animals might be (or might have been) less important in plants. We speculate that selection, if any, on genome configuration has taken a different turn after the divergence of plants and animals.

pyPaSWAS: Python-based multi-core CPU and GPU sequence alignment.

BACKGROUND: Our previously published CUDA-only application PaSWAS for Smith-Waterman (SW) sequence alignment of any type of sequence on NVIDIA-based GPUs is platform-specific and therefore adopted less than could be. The OpenCL language is supported more widely and allows use on a variety of hardware platforms. Moreover, there is a need to promote the adoption of parallel computing in bioinformatics by making its use and extension more simple through more and better application of high-level languages commonly used in bioinformatics, such as Python. RESULTS: The novel application pyPaSWAS presents the parallel SW sequence alignment code fully packed in Python. It is a generic SW implementation running on several hardware platforms with multi-core systems and/or GPUs that provides accurate sequence alignments that also can be inspected for alignment details. Additionally, pyPaSWAS support the affine gap penalty. Python libraries are used for automated system configuration, I/O and logging. This way, the Python environment will stimulate further extension and use of pyPaSWAS. CONCLUSIONS: pyPaSWAS presents an easy Python-based environment for accurate and retrievable parallel SW sequence alignments on GPUs and multi-core systems. The strategy of integrating Python with high-performance parallel compute languages to create a developer- and user-friendly environment should be considered for other computationally intensive bioinformatics algorithms.

A verification protocol for the probe sequences of Affymetrix genome arrays reveals high probe accuracy for studies in mouse, human and rat.

BACKGROUND: The Affymetrix GeneChip technology uses multiple probes per gene to measure its expression level. Individual probe signals can vary widely, which hampers proper interpretation. This variation can be caused by probes that do not properly match their target gene or that match multiple genes. To determine the accuracy of Affymetrix arrays, we developed an extensive verification protocol, for mouse arrays incorporating the NCBI RefSeq, NCBI UniGene Unique, NIA Mouse Gene Index, and UCSC mouse genome databases. RESULTS: Applying this protocol to Affymetrix Mouse Genome arrays (the earlier U74Av2 and the newer 430 2.0 array), the number of sequence-verified probes with perfect matches was no less than 85% and 95%, respectively; and for 74% and 85% of the probe sets all probes were sequence verified. The latter percentages increased to 80% and 94% after discarding one or two unverifiable probes per probe set, and even further to 84% and 97% when, in addition, allowing for one or two mismatches between probe and target gene. Similar results were obtained for other mouse arrays, as well as for human and rat arrays. Based on these data, refined chip definition files for all arrays are provided online. Researchers can choose the version appropriate for their study to (re)analyze expression data. CONCLUSION: The accuracy of Affymetrix probe sequences is higher than previously reported, particularly on newer arrays. Yet, refined probe set definitions have clear effects on the detection of differentially expressed genes. We demonstrate that the interpretation of the results of Affymetrix arrays is improved when the new chip definition files are used.

Similarities between plant traits based on their connection to underlying gene functions.

Understanding of phenotypes and their genetic basis is a major focus in current plant biology. Large amounts of phenotype data are being generated, both for macroscopic phenotypes such as size or yield, and for molecular phenotypes such as expression levels and metabolite levels. More insight in the underlying genetic and molecular mechanisms that influence phenotypes will enable a better understanding of how various phenotypes are related to each other. This will be a major step forward in understanding plant biology, with immediate value for plant breeding and academic plant research. Currently the genetic basis of most phenotypes remains however to be discovered, and the relatedness of different traits is unclear. We here present a novel approach to connect phenotypes to underlying biological processes and molecular functions. These connections define similarities between different types of phenotypes. The approach starts by using Quantitative Trait Locus (QTL) data, which are abundantly available for many phenotypes of interest. Overrepresentation analysis of gene functions based on Gene Ontology term enrichment across multiple QTL regions for a given phenotype, be it macroscopic or molecular, results in a small set of biological processes and molecular functions for each phenotype. Subsequently, similarity between different phenotypes can be defined in terms of these gene functions. Using publicly available rice data as example, a close relationship with defined molecular phenotypes is demonstrated for many macroscopic phenotypes. This includes for example a link between 'leaf senescence' and 'aspartic acid', as well as between 'days to maturity' and 'choline'. Relationships between macroscopic and molecular phenotypes may result in more efficient marker-assisted breeding and are likely to direct future research aimed at a better understanding of plant phenotypes.

Directed microspore-specific recombination of transgenic alleles to prevent pollen-mediated transmission of transgenes.

A major challenge for future genetically modified (GM) crops is to prevent undesired gene flow of transgenes to plant material intended for another use. Recombinase-mediated auto excision of transgenes directed by a tightly controlled microspore-specific promoter allows efficient removal of either the selectable marker gene or of all introduced transgenes during microsporogenesis. This way, transgene removal becomes an integral part of the biology of pollen maturation, not requiring any external stimulus such as chemical induction by spraying. We here show the feasibility of engineering transgenic plants to produce pollen devoid of any transgene. Highly efficient excision of transgenes from tobacco pollen was achieved with a potential failure rate of at most two out of 16,800 seeds (0.024%). No evidence for either premature activation or absence of activation of the recombinase system was observed under stress conditions in the laboratory. This approach can prevent adventitious presence of transgenes in non-GM crops or related wild species by gene flow. Such biological containment may help the deployment and management of coexistence practices to support consumer choice and will promote clean molecular farming for the production of high-value compounds in plants.

Assembly of two transgenes in an artificial chromatin domain gives highly coordinated expression in tobacco.

The chromatin loop model predicts that genes within the same chromatin domain exhibit coordinated regulation. We here present the first direct experimental support for this model in plants. Two reporter genes, the E. coli beta-glucuronidase gene and the firefly luciferase gene, driven by different promoters, were placed between copies of the chicken lysozyme A element, a member of the matrix-associated region (MAR) group of chromatin boundary elements, and introduced in tobacco (Nicotiana tabacum). In plants carrying A elements, quantitative enzyme activities and mRNA levels of both genes show high correlations compared to control plants. The A element thus creates an artificial chromatin domain that yields coordinated expression. Surprisingly, enzyme activities correlated poorly with their respective mRNA levels. We hypothesize that this indicates the occurrence of "error pipelines" in data generation: systematic errors of a given analytical method will point in the same direction and cancel out in correlation analysis, resulting in better correlations. In combining different methods of analysis, however, such errors do not cancel out and as a result relevant correlations can be masked. Such error pipelines will have to be taken into account when different types of (e.g., whole-genome) data sets are combined in quantitative analyses.

Flexible, fast and accurate sequence alignment profiling on GPGPU with PaSWAS.

MOTIVATION: To obtain large-scale sequence alignments in a fast and flexible way is an important step in the analyses of next generation sequencing data. Applications based on the Smith-Waterman (SW) algorithm are often either not fast enough, limited to dedicated tasks or not sufficiently accurate due to statistical issues. Current SW implementations that run on graphics hardware do not report the alignment details necessary for further analysis. RESULTS: With the Parallel SW Alignment Software (PaSWAS) it is possible (a) to have easy access to the computational power of NVIDIA-based general purpose graphics processing units (GPGPUs) to perform high-speed sequence alignments, and (b) retrieve relevant information such as score, number of gaps and mismatches. The software reports multiple hits per alignment. The added value of the new SW implementation is demonstrated with two test cases: (1) tag recovery in next generation sequence data and (2) isotype assignment within an immunoglobulin 454 sequence data set. Both cases show the usability and versatility of the new parallel Smith-Waterman implementation.

Allermatch, a webtool for the prediction of potential allergenicity according to current FAO/WHO Codex alimentarius guidelines.

BACKGROUND: Novel proteins entering the food chain, for example by genetic modification of plants, have to be tested for allergenicity. Allermatch http://allermatch.org is a webtool for the efficient and standardized prediction of potential allergenicity of proteins and peptides according to the current recommendations of the FAO/WHO Expert Consultation, as outlined in the Codex alimentarius. DESCRIPTION: A query amino acid sequence is compared with all known allergenic proteins retrieved from the protein databases using a sliding window approach. This identifies stretches of 80 amino acids with more than 35% similarity or small identical stretches of at least six amino acids. The outcome of the analysis is presented in a concise format. The predictive performance of the FAO/WHO criteria is evaluated by screening sets of allergens and non-allergens against the Allermatch databases. Besides correct predictions, both methods are shown to generate false positive and false negative hits and the outcomes should therefore be combined with other methods of allergenicity assessment, as advised by the FAO/WHO. CONCLUSIONS: Allermatch provides an accessible, efficient, and useful webtool for analysis of potential allergenicity of proteins introduced in genetically modified food prior to market release that complies with current FAO/WHO guidelines.

The promiscuity of heterospecific lox sites increases dramatically in the presence of palindromic DNA.

Heterospecific lox sites are mutated lox sites that in the presence of Cre recombinase recombine with themselves but not or much less with wildtype loxP. We here show that in Escherichia coli both lox511 and lox2272 sites become highly promiscuous with respect to loxP when in the presence of Cre one of the recombination partners is present in a larger stretch of an inverted repeat of non-lox DNA. In such a palindromic DNA configuration, also the occurrence of other DNA repeat-mediated recombination events is somewhat increased in the presence of Cre. The results indicate that in recombinase mediated cassette exchange or other double lox applications based on the exclusivity of heterospecific lox sites, or in research combining Cre-lox approaches with hairpin RNA for gene silencing, the presence of duplicated DNA around lox sites has to be taken into account. It is proposed that the presence of palindromic non-lox DNA interferes with the homology search of the Cre enzyme prior to the actual recombination event.

Seed-expressed fluorescent proteins as versatile tools for easy (co)transformation and high-throughput functional genomics in Arabidopsis.

We demonstrate that fluorescent proteins can be used as visual selection markers for the transformation of Arabidopsis thaliana by the floral dip method. Seed-specific expression of green fluorescent protein (GFP) variants, as well as DsRed, permits the identification of mature transformed seeds in a large background of untransformed seeds by fluorescence microscopy. In planta visualization of transformed seeds in siliques shows that susceptibility to floral dip transformation is limited to a small, defined window in flower development. In the competent stage, the random transformation of up to 25% of the seeds within a single silique may occur. The use of fluorescent proteins with different spectral characteristics allows a rapid identification and genetic analysis of seeds that have received multiple genes-of-interest in co-transformation experiments. The data reveal that co-transformation does not occur at random, since the co-transformed genes are integrated at a single genetic locus in approximately 70% of the cases. This genetic linkage of the co-transformed genes greatly simplifies metabolic pathway engineering by reverse genetics in Arabidopsis. Additional advantages of using visual selection instead of antibiotic resistance include a rapid identification of the effect of the T-DNA insertion or the transgene on seed development and/or germination. This technology, of tagging and identifying transformed seeds by fluorescence provides a novel high-throughput screening system with many potential applications in plant biotechnology.

Fast selection of miRNA candidates based on large-scale pre-computed MFE sets of randomized sequences.

BACKGROUND: Small RNAs are important regulators of genome function, yet their prediction in genomes is still a major computational challenge. Statistical analyses of pre-miRNA sequences indicated that their 2D structure tends to have a minimal free energy (MFE) significantly lower than MFE values of equivalently randomized sequences with the same nucleotide composition, in contrast to other classes of non-coding RNA. The computation of many MFEs is, however, too intensive to allow for genome-wide screenings. RESULTS: Using a local grid infrastructure, MFE distributions of random sequences were pre-calculated on a large scale. These distributions follow a normal distribution and can be used to determine the MFE distribution for any given sequence composition by interpolation. It allows on-the-fly calculation of the normal distribution for any candidate sequence composition. CONCLUSION: The speedup achieved makes genome-wide screening with this characteristic of a pre-miRNA sequence practical. Although this particular property alone will not be able to distinguish miRNAs from other sequences sufficiently discriminative, the MFE-based P-value should be added to the parameters of choice to be included in the selection of potential miRNA candidates for experimental verification.