Investigation of genetic variation in Jatropha curcas by Ecotilling and ISSR

The ability of species to adapt to different environments resides in their genetic diversity. This diversity, most commonly manifested as Single Nucleotide Polymorphisms (SNPs), can provide clues to the adaptive processes and population histories that have played a role in the species ’ evolution. A number of different techniques for identifying SNPs have been developed, all having their limitations. Reverse genetics approaches rely on the detection of sequence alterations in target genes to identify allelic variations in natural or mutant populations. Ecotilling, a variant of TILLING (Targeting Induced Local Lesions IN Genomes) technique, allows high-throughput analyses of natural genetic diversity in plants [1], particularly in species with limited genetic diversity. Jatropha curcas L. is a perennial, monoecious shrub of the Euphorbiaceae family, native to America but distributed widely in the tropical and subtropical areas [2]. Wild or semi-cultivated types of J. curcas can grow well under unfavourable climatic and soil conditions [3]. J. curcas has attracted a great deal of attention worldwide, regarding its potential as a new energy plant. The seeds of J. curcas contain 30-45 % oil [4] with a high percentage of monounsaturated oleic and polyunsaturated linoleic acid [5]. For genomic analyses, J. curcas is an interesting model species, since it has a relatively small genome (2C DNA content of 0.850 ± 0.006 pg or C DNA content of 0.416 × 109 bp) [6]. However, to achieve specific breeding goals in Jatropha for wider ecological adaptation, disease resistance and novel seed quality, the use of germplasm from different group and regions is necessary. Understandin

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

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

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

Discovery of nucleotide polymorphisms in the Musa gene pool by Ecotilling

Musa (banana and plantain) is an important genus for the global export market and in local markets where it provides staple food for approximately 400 million people. Hybridization and polyploidization of several (sub)species, combined with vegetative propagation and human selection have produced a complex genetic history. We describe the application of the Ecotilling method for the discovery and characterization of nucleotide polymorphisms in diploid and polyploid accessions of Musa. We discovered over 800 novel alleles in 80 accessions. Sequencing and band evaluation shows Ecotilling to be a robust and accurate platform for the discovery of polymorphisms in homologous and homeologous gene targets. In the process of validating the method, we identified two single nucleotide polymorphisms that may be deleterious for the function of a gene putatively important for phototropism. Evaluation of heterozygous polymorphism and haplotype blocks revealed a high level of nucleotide diversity in Musa accessions. We further applied a strategy for the simultaneous discovery of heterozygous and homozygous polymorphisms in diploid accessions to rapidly evaluate nucleotide diversity in accessions of the same genome type. This strategy can be used to develop hypotheses for inheritance patterns of nucleotide polymorphisms within and between genome types. We conclude that Ecotilling is suitable for diversity studies in Musa, that it can be considered for functional genomics studies and as tool in selecting germplasm for traditional and mutation breeding approaches

QTL×QTL×QTL Interaction Effects for Total Phenolic Content of Wheat Mapping Population of CSDH Lines under Drought Stress by Weighted Multiple Linear Regression

This paper proposes the use of weighted multiple linear regression to estimate the triple3interaction (additive×additive×additive) of quantitative trait loci (QTLs) effects. The use of unweighted regression yielded an improvement (in absolute value) in the QTL×QTL×QTL interaction effects compared to assessment based on phenotypes alone in three cases (severe drought in 2010, control in 2012 and severe drought in 2012). In contrast, weighted regression yielded an improvement (in absolute value) in the evaluation of the aaagw parameter compared to aaap in five cases, with the exception of severe drought in 2012. The results show that by using weighted regression on marker observations, the obtained estimates are closer to the ones obtained by the phenotypic method. The coefficients of determination for the weighted regression model were significantly higher than for the unweighted regression and ranged from 46.2% (control in 2010) to 95.0% (control in 2011). Considering this, it is clear that a three-way interaction had a significant effect on the expression of quantitative traits