Assessment of genetically modified soybean in relation to natural variation in the soybean seed metabolome.

Genetically modified (GM) crops currently constitute a significant and growing part of agriculture.An important aspect of GM crop adoption is to demonstrate safety; identifying differences in end points with respect to conventional crops is a part of the safety assessment process [corrected]. Untargeted metabolomics has the ability to profile diverse classes of metabolites and thus could be an adjunct for identification of differences between the GM crop and its conventional counterpart [corrected].To account for environmental effects and introgression of GM traits into diverse genetic backgrounds, we propose that the assessment for GM crop metabolic composition should be understood within the context of the natural variation for the crop. Using a non-targeted metabolomics platform, we profiled 169 metabolites and established their dynamic ranges from the seeds of 49 conventional soybean lines representing the current commercial genetic diversity. We further demonstrated that the metabolome of a GM line had no significant deviation from natural variation within the soybean metabolome, with the exception of changes in the targeted engineered pathway.

A large maize (Zea mays L.) SNP genotyping array: development and germplasm genotyping, and genetic mapping to compare with the B73 reference genome.

SNP genotyping arrays have been useful for many applications that require a large number of molecular markers such as high-density genetic mapping, genome-wide association studies (GWAS), and genomic selection. We report the establishment of a large maize SNP array and its use for diversity analysis and high density linkage mapping. The markers, taken from more than 800,000 SNPs, were selected to be preferentially located in genes and evenly distributed across the genome. The array was tested with a set of maize germplasm including North American and European inbred lines, parent/F1 combinations, and distantly related teosinte material. A total of 49,585 markers, including 33,417 within 17,520 different genes and 16,168 outside genes, were of good quality for genotyping, with an average failure rate of 4% and rates up to 8% in specific germplasm. To demonstrate this array's use in genetic mapping and for the independent validation of the B73 sequence assembly, two intermated maize recombinant inbred line populations - IBM (B73×Mo17) and LHRF (F2×F252) - were genotyped to establish two high density linkage maps with 20,913 and 14,524 markers respectively. 172 mapped markers were absent in the current B73 assembly and their placement can be used for future improvements of the B73 reference sequence. Colinearity of the genetic and physical maps was mostly conserved with some exceptions that suggest errors in the B73 assembly. Five major regions containing non-colinearities were identified on chromosomes 2, 3, 6, 7 and 9, and are supported by both independent genetic maps. Four additional non-colinear regions were found on the LHRF map only; they may be due to a lower density of IBM markers in those regions or to true structural rearrangements between lines. Given the array's high quality, it will be a valuable resource for maize genetics and many aspects of maize breeding.

GNC and CGA1 modulate chlorophyll biosynthesis and glutamate synthase (GLU1/Fd-GOGAT) expression in Arabidopsis.

Chloroplast development is an important determinant of plant productivity and is controlled by environmental factors including amounts of light and nitrogen as well as internal phytohormones including cytokinins and gibberellins (GA). The paralog GATA transcription factors GNC and CGA1/GNL up-regulated by light, nitrogen and cytokinin while also being repressed by GA signaling. Modifying the expression of these genes has previously been shown to influence chlorophyll content in Arabidopsis while also altering aspects of germination, elongation growth and flowering time. In this work, we also use transgenic lines to demonstrate that GNC and CGA1 exhibit a partially redundant control over chlorophyll biosynthesis. We provide novel evidence that GNC and CGA1 influence both chloroplast number and leaf starch in proportion to their transcript level. GNC and CGA1 were found to modify the expression of chloroplast localized GLUTAMATE SYNTHASE (GLU1/Fd-GOGAT), which is the primary factor controlling nitrogen assimilation in green tissue. Altering GNC and CGA1 expression was also found to modulate the expression of important chlorophyll biosynthesis genes (GUN4, HEMA1, PORB, and PORC). As previously demonstrated, the CGA1 transgenic plants demonstrated significantly altered timing to a number of developmental events including germination, leaf production, flowering time and senescence. In contrast, the GNC transgenic lines we analyzed maintain relatively normal growth phenotypes outside of differences in chloroplast development. Despite some evidence for partial divergence, results indicate that regulation of both GNC and CGA1 by light, nitrogen, cytokinin, and GA acts to modulate nitrogen assimilation, chloroplast development and starch production. Understanding the mechanisms controlling these processes is important for agricultural biotechnology.

Phenotypic analysis of Arabidopsis mutants: oomycete pathogens.

Various fungal pathogens are used in Arabidopsis pathogen studies, including Fusarium oxysporum, Alternaria brassicicola, Botrytis cinerea, and others. The oomycete pathogen Peronospora parasitica has been used by several groups and is described in this protocol. Working with Peronospora is complicated by the fact that it is an obligate biotroph, and consequently cultures must be maintained on living plants. There is no central repository for Peronospora stocks, but most investigators who work with them are willing to provide samples of infected tissue. These can be used to initiate new stock cultures, or they can be maintained as live cultures on seedlings. One of the most important factors in maintaining Peronospora is the humidity of the growth chamber, which must be kept at a minimum of 80%. Various Peronospora isolates are available. These vary with respect to which Arabidopsis ecotypes they can infect, because some combinations trigger gene-for-gene resistance. Thus, it is important that the appropriate ecotype is inoculated with the appropriate strain of pathogen. The extent of infections can be rated or quantitatively measured as the number of spores produced per plant, and frozen tissue stocks can be prepared from heavily infected tissue.

Microarray analysis of the transcriptome as a stepping stone towards understanding biological systems: practical considerations and perspectives.

DNA microarrays have been used to characterize plant transcriptomes to answer various biological questions. While many studies have provided significant insights, there has been great debate about the general reliability of the technology and data analysis. When compared to well-established transcript analysis technologies, such as RNA blot analysis or quantitative reverse transcription-PCR, discrepancies have frequently been observed. The reasons for these discrepancies often relate to the technical and experimental systems. This review-tutorial addresses common problems in microarray analysis and describes: (i) methods to maximize extraction of valuable biological information from the vast amount of microarray data and (ii) approaches to balance resource availability with high scientific standards and technological innovation with peer acceptability.

Fitness costs of mutations affecting the systemic acquired resistance pathway in Arabidopsis thaliana.

This study investigated the fitness effects of four mutations (npr1, cpr1, cpr5, and cpr6) and two transgenic genotypes (NPR1-L and NPR1-H) affecting different points of the systemic acquired resistance (SAR) signaling pathway associated with pathogen defense in Arabidopsis thaliana. The npr1 mutation, which resulted in a failure to express SAR, had no effect on fitness under growth chamber conditions, but decreased fitness in the field. The expression of NPR1 positively correlated with the fitness in the field. Constitutive activation of SAR by cpr1, cpr5, and cpr6 generally decreased fitness in the field and under two nutrient levels in two growth chamber conditions. At low-nutrient levels, fitness differences between wild type and the constitutive mutants were unchanged or reduced (especially in cpr5). The reduced fitness of the constitutive mutants suggests that this pathway is costly, with the precise fitness consequences highly dependent on the environmental context.

A network of rice genes associated with stress response and seed development.

We used a systematic approach to build a network of genes associated with developmental and stress responses in rice by identifying interaction domains for 200 proteins from stressed and developing tissues, by measuring the associated gene expression changes in different tissues exposed to a variety of environmental, biological, and chemical stress treatments, and by localizing the cognate genes to regions of stress-tolerance trait genetic loci. The integrated data set suggests that similar genes respond to environmental cues and stresses, and some may also regulate development. We demonstrate that the data can be used to correctly predict gene function in monocots and dicots. As a result, we have identified five genes that contribute to disease resistance in Arabidopsis.

A high-throughput Arabidopsis reverse genetics system.

A collection of Arabidopsis lines with T-DNA insertions in known sites was generated to increase the efficiency of functional genomics. A high-throughput modified thermal asymmetric interlaced (TAIL)-PCR protocol was developed and used to amplify DNA fragments flanking the T-DNA left borders from approximately 100000 transformed lines. A total of 85108 TAIL-PCR products from 52964 T-DNA lines were sequenced and compared with the Arabidopsis genome to determine the positions of T-DNAs in each line. Predicted T-DNA insertion sites, when mapped, showed a bias against predicted coding sequences. Predicted insertion mutations in genes of interest can be identified using Arabidopsis Gene Index name searches or by BLAST (Basic Local Alignment Search Tool) search. Insertions can be confirmed by simple PCR assays on individual lines. Predicted insertions were confirmed in 257 of 340 lines tested (76%). This resource has been named SAIL (Syngenta Arabidopsis Insertion Library) and is available to the scientific community at www.tmri.org.