Recognition and response to prospective competitors are crucial variables that must be considered in resource distribution and utilization in plant communities. Associated behaviors are largely mediated through the exchange of low-molecular weight exudates. These cues can significantly alter the root system architecture (RSA) between neighboring plants and are routinely sensitive enough to distinguish between plants of the same or different accessions, a phenomenon known as kin recognition (KR). Such refined discrimination of identity, based on the composition and detection of patterns of exudate signals is remarkable and provides insight into the chemical ecology of plant-plant interactions. The discovery that KR occurs in Arabidopsis thaliana provides a model system to resolve many of the mechanistic questions associated with this process. We hypothesized that the low-molecular weight cues which direct changes to the RSA during KR was driven by nutrient availability. Here we present evidence in support of a nutrient-inducible model for KR. Our findings underscore how exudate production and detection are influenced by nutrient availability as well as how this information is integrated into 'decisions' about competition and root system architecture which may have broader impacts on community composition.
Background: We are interested in understanding the locational distribution of genes and their functions in genomes, as this distribution has both functional and evolutionary significance. Gene locational distribution is known to be affected by various evolutionary processes, with tandem duplication thought to be the main process producing clustering of homologous sequences. Recent research has found clustering of protein structural families in the human genome, even when genes identified as tandem duplicates have been removed from the data. However, this previous research was hindered as they were unable to analyse small sample sizes. This is a challenge for bioinformatics as more specific functional classes have fewer examples and conventional statistical analyses of these small data sets often produces unsatisfactory results.
BackgroundComplex PCR applications for large genome-scale projects require fast, reliable and often highly sophisticated primer design software applications. Presently, such applications use pipelining methods to utilise many third party applications and this involves file parsing, interfacing and data conversion, which is slow and prone to error. A fully integrated suite of software tools for primer design would considerably improve the development time, the processing speed, and the reliability of bespoke primer design software applications.ResultsThe PD5 software library is an open-source collection of classes and utilities, providing a complete collection of software building blocks for primer design and analysis. It is written in object-oriented C++ with an emphasis on classes suitable for efficient and rapid development of bespoke primer design programs. The modular design of the software library simplifies the development of specific applications and also integration with existing third party software where necessary. We demonstrate several applications created using this software library that have already proved to be effective, but we view the project as a dynamic environment for building primer design software and it is open for future development by the bioinformatics community. Therefore, the PD5 software library is published under the terms of the GNU General Public License, which guarantee access to source-code and allow redistribution and modification.ConclusionsThe PD5 software library is downloadable from Google Code and the accompanying Wiki includes instructions and examples: http://code.google.com/p/primer-design
Many advances in synthetic biology require the removal of a large number of genomic elements from a genome. Most existing deletion methods leave behind markers, and as there are a limited number of markers, such methods can only be applied a fixed number of times. Deletion methods that recycle markers generally are either imprecise (remove untargeted sequences), or leave scar sequences which can cause genome instability and rearrangements. No existing marker recycling method is automation-friendly. We have developed a novel openly available deletion tool that consists of: 1) a method for deleting genomic elements that can be repeatedly used without limit, is precise, scar-free, and suitable for automation; and 2) software to design the method’s primers. Our tool is sequence agnostic and could be used to delete large numbers of coding sequences, promoter regions, transcription factor binding sites, terminators, etc in a single genome. We have validated our tool on the deletion of non-essential open reading frames (ORFs) from S. cerevisiae. The tool is applicable to arbitrary genomes, and we provide primer sequences for the deletion of: 90% of the ORFs from the S. cerevisiae genome, 88% of the ORFs from S. pombe genome, and 85% of the ORFs from the L. lactis genome.
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