T Radhakrishnan

Coat protein-mediated transgenic resistance of peanut (Arachis hypogaea L.) to peanut stem necrosis disease through Agrobacterium-mediated genetic transformation

The absence of resistance genes against biotic stresses like Tobacco streak virus (TSV) within compatible peanut germplasm necessitates the deployment of genetic engineering strategy to develop transgenic resistance. Transgenic resistance in peanut (Arachis hypogaea L.) to peanut stem necrosis disease caused by TSV was obtained by transferring coat protein (CP) gene of TSV through Agrobacterium-mediated transformation of de-embryonated cotyledons and immature leaves of peanut cultivars Kadiri 6 (K6) and Kadiri 134 (K134). Integration of the transgene in T1, T2 and T3 generations were confirmed by PCR with gene-specific primers. On the basis of segregation analysis of the PCR amplicons, homozygosity was confirmed in progeny from five transgenic lines. Six transgenic plants from three different single copy transgenic lines homozygous for the transgene were selected for challenge inoculation in T3 generations. The transgenic lines remained symptomless throughout and showed traces or no systemic accumulation of virus indicating the tolerance/resistance to the TSV infection. CP gene expression was observed in transgenic lines by RT-PCR, real-time PCR and ELISA. The findings provide an effective strategy for developing peanut with resistance to peanut stem necrosis disease.

Particle Swarm Optimization Technique Based Design of Pi Controller for a Real-Time Non-Linear Process

Abstract The increasing complexity of modern control systems has emphasized the idea of applying new approaches in order to solve design problems for different control engineering applications. Proportional-Integral-Derivative (PID) control schemes have been widely used in most of process control systems represented by chemical processes for a long time. However, a very important problem is how to determine or tune the PID parameters, because these parameters have a great influence on the stability and the performance of the control system. Computational intelligence (CI), which has caught the eyes of researchers due to its simplicity, low computational cost, and good performance, makes it a possible choice for tuning of PID controllers, to increase their performance. This paper discusses, in detail, the Particle Swarm Optimization (PSO) algorithm, a CI technique, and its implementation in PID tuning for a controller of a real time process. Compared to other conventional PID tuning methods, the result shows that better performance can be achieved with the proposed method. The ability of the designed controller, in terms of tracking set point, is also compared and simulation results are shown.

Overexpression of Bacterial mtlD Gene in Peanut Improves Drought Tolerance through Accumulation of Mannitol

In the changing global environmental scenarios, water scarcity and recurrent drought impose huge reductions to the peanut (Arachis hypogaea L.) crop yield. In plants, osmotic adjustments associated with efficient free radical scavenging ability during abiotic stress are important components of stress tolerance mechanisms. Mannitol, a compatible solute, is known to scavenge hydroxyl radicals generated during various abiotic stresses, thereby conferring tolerance to water-deficit stress in many plant species. However, peanut plant is not known to synthesize mannitol. Therefore, bacterial mtlD gene coding for mannitol 1-phosphate dehydrogenase under the control of constitutive promoter CaMV35S was introduced and overexpressed in the peanut cv. GG 20 using Agrobacterium tumefaciens-mediated transformation. A total of eight independent transgenic events were confirmed at molecular level by PCR, Southern blotting, and RT-PCR. Transgenic lines had increased amount of mannitol and exhibited enhanced tolerance in response to water-deficit stress. Improved performance of the mtlD transgenics was indicated by excised-leaf water loss assay and relative water content under water-deficit stress. Better performance of transgenics was due to the ability of the plants to synthesize mannitol. However, regulation of mtlD gene expression in transgenic plants remains to be elucidated.

Genomic Tools in Groundnut Breeding Program: Status and Perspectives

Groundnut, a nutrient-rich food legume, is cultivated world over. It is valued for its good quality cooking oil, energy and protein rich food, and nutrient-rich fodder. Globally, groundnut improvement programs have developed varieties to meet the preferences of farmers, traders, processors, and consumers. Enhanced yield, tolerance to biotic and abiotic stresses and quality parameters have been the target traits. Spurt in genetic information of groundnut was facilitated by development of molecular markers, genetic, and physical maps, generation of expressed sequence tags (EST), discovery of genes, and identification of quantitative trait loci (QTL) for some important biotic and abiotic stresses and quality traits. The first groundnut variety developed using marker assisted breeding (MAB) was registered in 2003. Since then, USA, China, Japan, and India have begun to use genomic tools in routine groundnut improvement programs. Introgression lines that combine foliar fungal disease resistance and early maturity were developed using MAB. Establishment of marker-trait associations (MTA) paved way to integrate genomic tools in groundnut breeding for accelerated genetic gain. Genomic Selection (GS) tools are employed to improve drought tolerance and pod yield, governed by several minor effect QTLs. Draft genome sequence and low cost genotyping tools such as genotyping by sequencing (GBS) are expected to accelerate use of genomic tools to enhance genetic gains for target traits in groundnut.

Molecular characterisation of Aspergillus flavus isolates from peanut fields in India using AFLP

Aflatoxin contamination of peanut, due to infection by Aspergillus flavus, is a major problem of rain-fed agriculture in India. In the present study, molecular characterisation of 187 Aspergillus flavus isolates, which were sampled from the peanut fields of Gujarat state in India, was performed using AFLP markers. On a pooled cluster analysis, the markers could successfully discriminate among the ‘A’, ‘B’ and ‘G’ group A. flavus isolates. PCoA analysis also showed equivalent results to the cluster analysis. Most of the isolates from one district could be clustered together, which indicated genetic similarity among the isolates. Further, a lot of genetic variability was observed within a district and within a group. The results of AMOVA test revealed that the variance within a population (84%) was more than that between two populations (16%). The isolates, when tested by indirect competitive ELISA, showed about 68.5% of them to be atoxigenic. Composite analysis between the aflatoxin production and AFLP data was found to be ineffective in separating the isolate types by aflatoxigenicity. Certain unique fragments, with respect to individual isolates, were also identified that may be used for development of SCAR marker to aid in rapid and precise identification of isolates.

Individual and consensus QTL maps of Groundnut from ICGS76 X CSMG84-1, ICGS44 X ICGS76 and TAG24 X ICGV86031

With the aim of understanding the genetic basis and identification of quantitative trait loci (QTL) for drought tolerance, two new recombinant inbred line (RIL) mapping populations, namely ICGS 76 × CSMG 84-1 (RIL-2) and ICGS 44 × ICGS 76 (RIL-3), were used. CMap Visualization Links: ICGS76 X CSMG84-1 ICGS44 X ICGS76 TAG24 X ICGV86031 DOI: doi:10.1007/s11032-011-9660-0