Identification of Rf9, a Gene Contributing to the Genetic Complexity of Fertility Restoration in Hybrid Wheat.

Wheat (Triticum aestivum L.) is a self-pollinating crop whose hybrids offer the potential to provide a major boost in yield. Male sterility induced by the cytoplasm of Triticum timopheevii is a powerful method for hybrid seed production. Hybrids produced by this method are often partially sterile, and full fertility restoration is crucial for wheat production using hybrid cultivars. To identify the genetic loci controlling fertility restoration in wheat, we produced two cytoplasmic male-sterile (CMS) backcross (BC1) mapping populations. The restorer lines Gerek 79 and 71R1203 were used to pollinate the male-sterile winter wheat line CMS-Sperber. Seed set and numbers of sterile spikelets per spike were evaluated in 340 and 206 individuals of the populations derived from Gerek 79 and 71R1203, respectively. Genetic maps were constructed using 930 and 994 single nucleotide polymorphism (SNP) markers, spanning 2,160 and 2,328 cM over 21 linkage groups in the two populations, respectively. Twelve quantitative trait loci (QTL) controlled fertility restoration in both BC1 populations, including a novel restorer-of-fertility (Rf) locus flanked by the SNP markers IWB72413 and IWB1550 on chromosome 6AS. The locus was mapped as a qualitative trait in the BC1 Gerek 79 population and was designated Rf9. One hundred-nineteen putative candidate genes were predicted within the QTL region on chromosome 6AS. Among them were genes encoding mitochondrial transcription termination factor and pentatricopeptide repeat-containing proteins that are known to be associated with fertility restoration. This finding is a promising step to better understand the functions of genes for improving fertility restoration in hybrid wheat.

The GMOseek matrix: a decision support tool for optimizing the detection of genetically modified plants.

BACKGROUND: Since their first commercialization, the diversity of taxa and the genetic composition of transgene sequences in genetically modified plants (GMOs) are constantly increasing. To date, the detection of GMOs and derived products is commonly performed by PCR-based methods targeting specific DNA sequences introduced into the host genome. Information available regarding the GMOs' molecular characterization is dispersed and not appropriately organized. For this reason, GMO testing is very challenging and requires more complex screening strategies and decision making schemes, demanding in return the use of efficient bioinformatics tools relying on reliable information. DESCRIPTION: The GMOseek matrix was built as a comprehensive, online open-access tabulated database which provides a reliable, comprehensive and user-friendly overview of 328 GMO events and 247 different genetic elements (status: 18/07/2013). The GMOseek matrix is aiming to facilitate GMO detection from plant origin at different phases of the analysis. It assists in selecting the targets for a screening analysis, interpreting the screening results, checking the occurrence of a screening element in a group of selected GMOs, identifying gaps in the available pool of GMO detection methods, and designing a decision tree. The GMOseek matrix is an independent database with effective functionalities in a format facilitating transferability to other platforms. Data were collected from all available sources and experimentally tested where detection methods and certified reference materials (CRMs) were available. CONCLUSIONS: The GMOseek matrix is currently a unique and very valuable tool with reliable information on GMOs from plant origin and their present genetic elements that enables further development of appropriate strategies for GMO detection. It is flexible enough to be further updated with new information and integrated in different applications and platforms.

Development and validation of duplex, triplex, and pentaplex real-time PCR screening assays for the detection of genetically modified organisms in food and feed.

Worldwide, qualitative methods based on PCR are most commonly used as screening tools for genetically modified material in food and feed. However, the increasing number and diversity of genetically modified organisms (GMO) require effective methods for simultaneously detecting several genetic elements marking the presence of transgenic events. Herein we describe the development and validation of a pentaplex, as well as complementary triplex and duplex real-time PCR assays, for the detection of the most common screening elements found in commercialized GMOs: P-35S, T-nos, ctp2-cp4-epsps, bar, and pat. The use of these screening assays allows the coverage of many GMO events globally approved for commercialization. Each multiplex real-time PCR assay shows high specificity and sensitivity with an absolute limit of detection below 20 copies for the targeted sequences. We demonstrate by intra- and interlaboratory tests that the assays are robust as well as cost- and time-effective for GMO screening if applied in routine GMO analysis.

Determination of detection and quantification limits for SNP allele frequency estimation in DNA pools using real time PCR.

The quantification of single nucleotide polymorphism (SNP) allele frequencies in pooled DNA samples using real time PCR is a promising approach for large-scale diagnostics and genotyping. The limits of detection (LOD) and limits of quantification (LOQ) for mutant SNP alleles are of particular importance for determination of the working range, which, in the case of allele-specific real time PCR, can be limited by the variance of calibration data from serially diluted mutant allele samples as well as by the variance of the 100% wild-type allele samples (blank values). In this study, 3sigma and 10sigma criteria were applied for the calculation of LOD and LOQ values. Alternatively, LOQ was derived from a 20% threshold for the relative standard deviation (%RSD) of measurements by fitting a curve for the relationship between %RSD and copy numbers of the mutant alleles. We found that detection and quantification of mutant alleles were exclusively limited by the variance of calibration data since the estimated LOD(calibration) (696 in 30 000 000 copies, 0.0023%), LOQ(20%RSD) (1470, 0.0049%) and LOQ(calibration) (2319, 0.0077) values were significantly higher than the LOD(blank) (130, 0.0004%) and LOQ(blank) (265, 0.0009%) values derived from measurements of wild-type allele samples. No significant matrix effects of the genomic background DNA on the estimation of LOD and LOQ were found. Furthermore, the impact of large genome sizes and the general application of the procedure for the estimation of LOD and LOQ in quantitative real time PCR diagnostics are discussed.