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Abstract Background Recent advances in sequencing techniques leading to cost reduction have resulted in the generation of a growing number of sequenced eukaryotic genomes. Computational tools greatly assist in defining open reading frames and assigning tentative annotations. However, gene functions cannot be asserted without biological support through, among other things, mutational analysis. In taking a genome-wide approach to functionally annotate an entire organism, in this application the ~11,000 predicted genes in the rice blast fungus (Magnaporthe grisea), an effective platform for tracking and storing both the biological materials created and the data produced across several participating institutions was required. Results The platform designed, named PACLIMS, was built to support our high throughput pipeline for generating 50,000 random insertion mutants of Magnaporthe grisea. To be a useful tool for materials and data tracking and storage, PACLIMS was designed to be simple to use, modifiable to accommodate refinement of research protocols, and cost-efficient. Data entry into PACLIMS was simplified through the use of barcodes and scanners, thus reducing the potential human error, time constraints, and labor. This platform was designed in concert with our experimental protocol so that it leads the researchers through each step of the process from mutant generation through phenotypic assays, thus ensuring that every mutant produced is handled in an identical manner and all necessary data is captured. Conclusion Many sequenced eukaryotes have reached the point where computational analyses are no longer sufficient and require biological support for their predicted genes. Consequently, there is an increasing need for platforms that support high throughput genome-wide mutational analyses. While PACLIMS was designed specifically for this project, the source and ideas present in its implementation can be used as a model for other high throughput mutational endeavors.

We describe here the analysis of random T-DNA insertions that were generated as part of a large-scale insertional mutagenesis project for Magnaporthe oryzae. Chromosomal regions flanking T-DNA insertions were rescued by inverse PCR, sequenced and used to search the M. oryzae genome assembly. Among the 175 insertions for which at least one flank was rescued, 137 had integrated in single-copy regions of the genome, 17 were in repeated sequences, one had no match to the genome, and the remainder were unassigned due to illegitimate T-DNA integration events. These included in order of abundance: head-to-tail tandem insertions, right border excision failures, left border excision failures and insertion of one T-DNA into another. The left borders of the T-DNA were frequently truncated and inserted in sequences with micro-homology to the left terminus. By contrast the right borders were less prone to degradation and appeared to have been integrated in a homology-independent manner. Gross genome rearrangements rarely occurred when the T-DNAs integrated in single-copy regions, although most insertions did cause small deletions at the target site. Significant insertion bias was detected, with promoters receiving two times more T-DNA hits than expected, and open reading frames receiving three times fewer. In addition, we found that the distribution of T-DNA inserts among the M. oryzae chromosomes was not random. The implications of these findings with regard to saturation mutagenesis of the M. oryzae genome are discussed.

Towards the goal of disrupting all genes in the genome of Magnaporthe oryzae and identifying their function, a collection of >55,000 random insertion lines of M. oryzae strain 70-15 were generated. All strains were screened to identify genes involved in growth rate, conidiation, pigmentation, auxotrophy, and pathogenicity. Here, we provide a description of the high throughput transformation and analysis pipeline used to create our library. Transformed lines were generated either by CaCl(2)/PEG treatment of protoplasts with DNA or by Agrobacterium tumefaciens-mediated transformation (ATMT). We describe the optimization of both approaches and compare their efficiency. ATMT was found to be a more reproducible method, resulting in predominantly single copy insertions, and its efficiency was high with up to 0.3% of conidia being transformed. The phenotypic data is accessible via a public database called MGOS and all strains are publicly available. This represents the most comprehensive insertional mutagenesis analysis of a fungal pathogen.

Background: Recent advances in sequencing techniques leading to cost reduction have resulted in the generation of a growing number of sequenced eukaryotic genomes. Computational tools greatly assist in defining open reading frames and assigning tentative annotations. However, gene functions cannot be asserted without biological support through, among other things, mutational analysis. In taking a genome-wide approach to functionally annotate an entire organism, in this application the approximately 11,000 predicted genes in the rice blast fungus (Magnaporthe grisea), an effective platform for tracking and storing both the biological materials created and the data produced across several participating institutions was required., Results: The platform designed, named PACLIMS, was built to support our high throughput pipeline for generating 50,000 random insertion mutants of Magnaporthe grisea. To be a useful tool for materials and data tracking and storage, PACLIMS was designed to be simple to use, modifiable to accommodate refinement of research protocols, and cost-efficient. Data entry into PACLIMS was simplified through the use of barcodes and scanners, thus reducing the potential human error, time constraints, and labor. This platform was designed in concert with our experimental protocol so that it leads the researchers through each step of the process from mutant generation through phenotypic assays, thus ensuring that every mutant produced is handled in an identical manner and all necessary data is captured., Conclusion: Many sequenced eukaryotes have reached the point where computational analyses are no longer sufficient and require biological support for their predicted genes. Consequently, there is an increasing need for platforms that support high throughput genome-wide mutational analyses. While PACLIMS was designed specifically for this project, the source and ideas present in its implementation can be used as a model for other high throughput mutational endeavors.