Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data.
The extensive subcellular compartmentalization of metabolites and metabolism in eukaryotic cells is widely acknowledged and represents a key factor of metabolic activity and functionality. In striking contrast, the knowledge of actual compartmental distribution of metabolites from experimental studies is surprisingly low. However, a precise knowledge of, possibly all, metabolites and their subcellular distributions remains a key prerequisite for the understanding of any cellular function.
High-throughput measurement of transcript intensities using Affymetrix type oligonucleotide microarrays has produced a massive quantity of data during the last decade. Different preprocessing techniques exist to convert the raw signal intensities measured by these chips into gene expression estimates. Although these techniques have been widely benchmarked in the context of differential gene expression analysis, there are only few examples where their performance has been assessed in respect to coexpression-based studies such as sample classification.
Very few reports have studied the interactions between ascorbate and fruit metabolism. In order to get insights into the complex relationships between ascorbate biosynthesis/recycling and other metabolic pathways in the fruit, we undertook a fruit systems biology approach. To this end, we have produced tomato transgenic lines altered in ascorbate content and redox ratio by RNAi-targeting several key enzymes involved in ascorbate biosynthesis (2 enzymes) and recycling (2 enzymes). In the VTC (ViTamin C) Fruit project, we then generated phenotypic and genomic (transcriptome, proteome, metabolome) data from wild type and mutant tomato fruit at two stages of fruit development, and developed or implemented statistical and bioinformatic tools as a web application (named VTC Tool box) necessary to store, analyse and integrate experimental data in tomato. By using Kohonens self-organizing maps (SOMs) to cluster the biological data, pair-wise Pearson correlation analyses and simultaneous visualization of transcript/protein and metabolites (MapMan), this approach allowed us to uncover major relationships between ascorbate and other metabolic pathways.
Indole Acetic Acid 9 (IAA9) is a negative auxin response regulator belonging to the Aux/IAA transcription factor gene family whose downregulation triggers fruit set before pollination, thus giving rise to parthenocarpy. In situ hybridization experiments revealed that a tissue-specific gradient of IAA9 expression is established during flower development, the release of which upon pollination triggers the initiation of fruit development. Comparative transcriptome and targeted metabolome analysis uncovered important features of the molecular events underlying pollination-induced and pollination-independent fruit set. Comprehensive transcriptomic profiling identified a high number of genes common to both types of fruit set, among which only a small subset are dependent on IAA9 regulation. The fine-tuning of Aux/IAA and ARF genes and the downregulation of TAG1 and TAGL6 MADS box genes are instrumental in triggering the fruit set program. Auxin and ethylene emerged as the most active signaling hormones involved in the flower-to-fruit transition. However, while these hormones affected only a small number of transcriptional events, dramatic shifts were observed at the metabolic and developmental levels. The activation of photosynthesis and sucrose metabolism-related genes is an integral regulatory component of fruit set process. The combined results allow a far greater comprehension of the regulatory and metabolic events controlling early fruit development both in the presence and absence of pollination/fertilization.
The methylesterification status of cell wall homogalacturonans, mediated through the action of pectin methylesterases (PMEs), influences the biophysical properties of plant cell walls such as elasticity and porosity, important parameters for cell elongation and water uptake. The completion of seed germination requires cell wall extensibility changes in both the radicle itself and in the micropylar tissues surrounding the radicle. In wild-type seeds of Arabidopsis (Arabidopsis thaliana), PME activities peaked around the time of testa rupture but declined just before the completion of germination (endosperm weakening and rupture). We overexpressed an Arabidopsis PME inhibitor to investigate PME involvement in seed germination. Seeds of the resultant lines showed a denser methylesterification status of their cell wall homogalacturonans, but there were no changes in the neutral sugar and uronic acid composition of the cell walls. As compared with wild-type seeds, the PME activities of the overexpressing lines were greatly reduced throughout germination, and the low steady-state levels neither increased nor decreased. The most striking phenotype was a significantly faster rate of germination, which was not connected to altered testa rupture morphology but to alterations of the micropylar endosperm cells, evident by environmental scanning electron microscopy. The transgenic seeds also exhibited an apparent reduced sensitivity to abscisic acid with respect to its inhibitory effects on germination. We speculate that PME activity contributes to the temporal regulation of radicle emergence in endospermic seeds by altering the mechanical properties of the cell walls and thereby the balance between the two opposing forces of radicle elongation and mechanical resistance of the endosperm.
Related JoVE Video
Journal of Visualized Experiments
What is Visualize?
JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.
How does it work?
We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.
Video X seems to be unrelated to Abstract Y...
In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.