Optimizing TILLING and Ecotilling techniques for potato (Solanum tuberosum L)

<p>Abstract</p> <p>Background</p> <p>The TILLING and Ecotilling techniques for the discovery of nucleotide polymorphisms were applied to three potato (<it>Solanum tuberosum</it>) cultivars treated with gamma irradiation. The three mutant cultivars tested were previously shown to exhibit salinity tolerance, an important trait in countries like Syria where increasing soil salinity is affecting agricultural production.</p> <p>Findings</p> <p>Three gene-specific primer pairs were designed from BAC sequence to amplify ~1 to 1.5 kb of gene target. One of the three primer pairs amplified a single gene target. We used this primer pair to optimize enzymatic mismatch cleavage and fluorescence DNA detection for polymorphism discovery. We identified 15 putative nucleotide polymorphisms per kilobase. Nine discovered polymorphisms were unique to one of the three tetraploid cultivars tested.</p> <p>Conclusion</p> <p>This work shows the utility of enzymatic mismatch cleavage for TILLING and Ecotilling in different varieties of potato. The method allows for rapid germplasm characterization without the cost and high informatics load of DNA sequencing. It is also suitable for mutation discovery in high-throughput reverse genetic screens.</p

High-throughput discovery of rare human nucleotide polymorphisms by Ecotilling

Human individuals differ from one another at only ∼0.1% of nucleotide positions, but these single nucleotide differences account for most heritable phenotypic variation. Large-scale efforts to discover and genotype human variation have been limited to common polymorphisms. However, these efforts overlook rare nucleotide changes that may contribute to phenotypic diversity and genetic disorders, including cancer. Thus, there is an increasing need for high-throughput methods to robustly detect rare nucleotide differences. Toward this end, we have adapted the mismatch discovery method known as Ecotilling for the discovery of human single nucleotide polymorphisms. To increase throughput and reduce costs, we developed a universal primer strategy and implemented algorithms for automated band detection. Ecotilling was validated by screening 90 human DNA samples for nucleotide changes in 5 gene targets and by comparing results to public resequencing data. To increase throughput for discovery of rare alleles, we pooled samples 8-fold and found Ecotilling to be efficient relative to resequencing, with a false negative rate of 5% and a false discovery rate of 4%. We identified 28 new rare alleles, including some that are predicted to damage protein function. The detection of rare damaging mutations has implications for models of human disease

Genetic Variability Induced by Gamma Rays and Preliminary Results of Low-Cost TILLING on M2 Generation of Chickpea (Cicer arietinum L.)

In order to increase genetic variability for chickpea improvement, the Kabuli genotype, variety Ghab4, was treated with 280 Grays of gamma rays (Cobalt 60). Field characterization began with the M2 generation. A total of 135 M2 families were sown in the field resulting in approximately 4,000 plants. Traits related to phenology (days to flowering, days to maturity), plant morphology of vegetative parts (plant height, height of first pod, number of primary branches per plant) and yield (number of seeds per pod, total number of pods per plant, total number of seeds per plant, seed yield and hundred seed weight) were recorded and analyzed to evaluate genetic variability. An evaluation of the efficacy of low-cost TILLING (Targeting Induced Local Lesions IN Genomes) to discover mutations in the M2 generation was undertaken. Mutation screening focused on genes involved in resistance to two important diseases of chickpea; Ascochyta blight (AB) and Fusarium wilt (FW), as well as genes responsible for early flowering. Analysis of variance showed a highly significant difference among mutant families for all studied traits. The higher estimates of genetic parameters (genotypic and phenotypic coefficient of variation, broad sense heritability and genetic advance) were recorded for number of seeds per plant and yield. Total yield was highly significant and positively correlated with number of pods and seeds per plant. Path analysis revealed that the total number of seeds per plant had the highest positive direct effect followed by hundred seed weight parameter. One cluster from nine exhibited the highest mean values for total number of pods and seeds per plant as well as yield per plant. According to Dunnett’s test, 37 M2 families superior to the control were determined for five agronomical traits. Pilot experiments with low-cost TILLING show that the seed stock used for mutagenesis is homogeneous and that small mutations do not predominate at the dosage used

Low-Cost Methods for Molecular Characterization of Mutant Plants: Tissue Desiccation, DNA Extraction and Mutation Discovery: Protocols

Plant Breeding/Biotechnology; Biological Techniques; Nucleic Acid Chemistr

Discovery of chemically induced mutations in rice by TILLING

BACKGROUND: Rice is both a food source for a majority of the world's population and an important model system. Available functional genomics resources include targeted insertion mutagenesis and transgenic tools. While these can be powerful, a non-transgenic, unbiased targeted mutagenesis method that can generate a range of allele types would add considerably to the analysis of the rice genome. TILLING (Targeting Induced Local Lesions in Genomes), a general reverse genetic technique that combines traditional mutagenesis with high throughput methods for mutation discovery, is such a method. RESULTS: To apply TILLING to rice, we developed two mutagenized rice populations. One population was developed by treatment with the chemical mutagen ethyl methanesulphonate (EMS), and the other with a combination of sodium azide plus methyl-nitrosourea (Az-MNU). To find induced mutations, target regions of 0.7–1.5 kilobases were PCR amplified using gene specific primers labeled with fluorescent dyes. Heteroduplexes were formed through denaturation and annealing of PCR products, mismatches digested with a crude preparation of CEL I nuclease and cleaved fragments visualized using denaturing polyacrylamide gel electrophoresis. In 10 target genes screened, we identified 27 nucleotide changes in the EMS-treated population and 30 in the Az-MNU population. CONCLUSION: We estimate that the density of induced mutations is two- to threefold higher than previously reported rice populations (about 1/300 kb). By comparison to other plants used in public TILLING services, we conclude that the populations described here would be suitable for use in a large scale TILLING project

Is it the end of TILLING era in plant science?

Since its introduction in 2000, the TILLING strategy has been widely used in plant research to create novel genetic diversity. TILLING is based on chemical or physical mutagenesis followed by the rapid identification of mutations within genes of interest. TILLING mutants may be used for functional analysis of genes and being nontransgenic, they may be directly used in pre-breeding programs. Nevertheless, classical mutagenesis is a random process, giving rise to mutations all over the genome. Therefore TILLING mutants carry background mutations, some of which may affect the phenotype and should be eliminated, which is often time-consuming. Recently, new strategies of targeted genome editing, including CRISPR/Cas9-based methods, have been developed and optimized for many plant species. These methods precisely target only genes of interest and produce very few off-targets. Thus, the question arises: is it the end of TILLING era in plant studies? In this review, we recap the basics of the TILLING strategy, summarize the current status of plant TILLING research and present recent TILLING achievements. Based on these reports, we conclude that TILLING still plays an important role in plant research as a valuable tool for generating genetic variation for genomics and breeding projects

Low-Cost Methods for Molecular Characterization of Mutant Plants: Tissue Desiccation, DNA Extraction and Mutation Discovery: Protocols

Plant Breeding/Biotechnology; Biological Techniques; Nucleic Acid Chemistr

Treatment-aware Diffusion Probabilistic Model for Longitudinal MRI Generation and Diffuse Glioma Growth Prediction

Diffuse gliomas are malignant brain tumors that grow widespread through the brain. The complex interactions between neoplastic cells and normal tissue, as well as the treatment-induced changes often encountered, make glioma tumor growth modeling challenging. In this paper, we present a novel end-to-end network capable of generating future tumor masks and realistic MRIs of how the tumor will look at any future time points for different treatment plans. Our approach is based on cutting-edge diffusion probabilistic models and deep-segmentation neural networks. We included sequential multi-parametric magnetic resonance images (MRI) and treatment information as conditioning inputs to guide the generative diffusion process. This allows for tumor growth estimates at any given time point. We trained the model using real-world postoperative longitudinal MRI data with glioma tumor growth trajectories represented as tumor segmentation maps over time. The model has demonstrated promising performance across a range of tasks, including the generation of high-quality synthetic MRIs with tumor masks, time-series tumor segmentations, and uncertainty estimates. Combined with the treatment-aware generated MRIs, the tumor growth predictions with uncertainty estimates can provide useful information for clinical decision-making.Comment: 13 pages, 10 figures, 2 tables, 2 agls, preprints in the IEEE trans. format for submission to IEEE-TM