Assessment of pleiotropic transcriptome perturbations in Arabidopsis engineered for indirect insect defence

A Comparison of transgenic and wild type soybean seeds: analysis of transcriptome profiles using RNA-Seq

BACKGROUND

Soybean (Glycine max) has been bred for thousands of years to produce seeds rich in protein for human and animal consumption, making them an appealing bioreactor for producing valuable recombinant proteins at high levels. However, the effects of expressing recombinant protein at high levels on bean physiology are not well understood. To address this, we investigated whether gene expression within transgenic soybean seed tissue is altered when large amounts of recombinant proteins are being produced and stored exclusively in the seeds. We used RNA-Seq to survey gene expression in three transgenic soybean lines expressing recombinant protein at levels representing up to 1.61 % of total protein in seed tissues. The three lines included: ST77, expressing human thyroglobulin protein (hTG), ST111, expressing human myelin basic protein (hMBP), and 764, expressing a mutant, nontoxic form of a staphylococcal subunit vaccine protein (mSEB). All lines selected for analysis were homozygous and contained a single copy of the transgene.

METHODS

Each transgenic soybean seed was screened for transgene presence and recombinant protein expression via PCR and western blotting.  Whole seed mRNA was extracted and cDNA libraries constructed for Illumina sequencing.  Following alignment to the soybean reference genome, differential gene expression analysis was conducted using edgeR and cufflinks.  Functional analysis of differentially expressed genes was carried out using the gene ontology analysis tool AgriGO.

RESULTS

The transcriptomes of nine seeds from each transgenic line were sequenced and compared with wild type seeds. Native soybean gene expression was significantly altered in line 764 (mSEB) with more than 3000 genes being upregulated or downregulated. ST77 (hTG) and ST111 (hMBP) had significantly less differences with 52 and 307 differentially expressed genes respectively. Gene ontology enrichment analysis found that the upregulated genes in the 764 line were annotated with functions related to endopeptidase inhibitors and protein synthesis, but suppressed expression of genes annotated to the nuclear pore and to protein transport. No significant gene ontology terms were detected in ST77, and only a few genes involved in photosynthesis and thylakoid functions were downregulated in ST111. Despite these differences, transgenic plants and seeds appeared phenotypically similar to non-transgenic controls. There was no correlation between recombinant protein expression level and the quantity of differentially expressed genes detected.

CONCLUSIONS

Measurable unscripted gene expression changes were detected in the seed transcriptomes of all three transgenic soybean lines analyzed, with line 764 being substantially altered. Differences detected at the transcript level may be due to T-DNA insert locations, random mutations following transformation or direct effects of the recombinant protein itself, or a combination of these. The physiological consequences of such changes remain unknown.

CONTRAILS: A tool for rapid identification of transgene integration sites in complex, repetitive genomes using low-coverage paired-end sequencing

Transgenic crops have become a staple in modern agriculture, and are typically characterized using a variety of molecular techniques involving proteomics and metabolomics. Characterization of the transgene insertion site is of great interest, as disruptions, deletions, and genomic location can affect product selection and fitness, and identification of these regions and their integrity is required for regulatory agencies. Here, we present CONTRAILS (Characterization of Transgene Insertion Locations with Sequencing), a straightforward, rapid and reproducible method for the identification of transgene insertion sites in highly complex and repetitive genomes using low coverage paired-end Illumina sequencing and traditional PCR. This pipeline requires little to no troubleshooting and is not restricted to any genome type, allowing use for many molecular applications. Using whole genome sequencing of in-house transgenic Glycine max, a legume with a highly repetitive and complex genome, we used CONTRAILS to successfully identify the location of a single T-DNA insertion to single base resolution.

•

We developed a pipeline for transgene identification using paired-end sequencing.

•

This method requires little troubleshooting and is applicable to any genome.

•

Identification of insertion sites is required for deregulation of modified food crops.

•

This assists in identifying potential genomic disruptions in transgenic events.

Multidimensional approaches for studying plant defence against insects: from ecology to omics and synthetic biology

The biggest challenge for modern biology is to integrate multidisciplinary approaches towards understanding the organizational and functional complexity of biological systems at different hierarchies, starting from the subcellular molecular mechanisms (microscopic) to the functional interactions of ecological communities (macroscopic). The plant-insect interaction is a good model for this purpose with the availability of an enormous amount of information at the molecular and the ecosystem levels. Changing global climatic conditions are abruptly resetting plant-insect interactions. Integration of discretely located heterogeneous information from the ecosystem to genes and pathways will be an advantage to understand the complexity of plant-insect interactions. This review will present the recent developments in omics-based high-throughput experimental approaches, with particular emphasis on studying plant defence responses against insect attack. The review highlights the importance of using integrative systems approaches to study plant-insect interactions from the macroscopic to the microscopic level. We analyse the current efforts in generating, integrating and modelling multiomics data to understand plant-insect interaction at a systems level. As a future prospect, we highlight the growing interest in utilizing the synthetic biology platform for engineering insect-resistant plants.