Jawaharlal Nehru University

About: Jawaharlal Nehru University is a education organization based out in New Delhi, India. It is known for research contribution in the topics: Population & Politics. The organization has 6082 authors who have published 13455 publications receiving 245407 citations. The organization is also known as: JNU.

Tomato cultivar tolerant to Tomato leaf curl New Delhi virus infection induces virus-specific short interfering RNA accumulation and defence-associated host gene expression

Abstract: Tomato leaf curl New Delhi virus (ToLCNDV) infection causes significant yield loss in tomato. The availability of a conventional tolerance source against this virus is limited in tomato. To understand the molecular mechanism of virus tolerance in tomato, the abundance of viral genomic replicative intermediate molecules and virus-directed short interfering RNAs (siRNAs) by the host plant in a naturally tolerant cultivar H-88-78-1 and a susceptible cultivar Punjab Chhuhara at different time points after agroinfection was studied. We report that less abundance of viral replicative intermediate in the tolerant cultivar may have a correlation with a relatively higher accumulation of virus-specific siRNAs. To study defence-related host gene expression in response to ToLCNDV infection, the suppression subtractive hybridization technique was used. A library was prepared from tolerant cultivar H-88-78-1 between ToLCNDV-inoculated and Agrobacterium mock-inoculated plants of this cultivar at 21 days post-inoculation (dpi). A total of 106 nonredundant transcripts was identified and classified into 12 different categories according to their putative functions. By reverse Northern analysis and quantitative real-time polymerase chain reaction (qRT-PCR), we identified the differential expression pattern of 106 transcripts, 34 of which were up-regulated (>2.5-fold induction). Of these, eight transcripts showed more than four fold induction. qRT-PCR analysis was carried out to obtain comparative expression profiling of these eight transcripts between Punjab Chhuhara and H-88-78-1 on ToLCNDV infection. The expression patterns of these transcripts showed a significant increase in differential expression in the tolerant cultivar, mostly at 14 and 21 dpi, in comparison with that in the susceptible cultivar, as analysed by qRT-PCR. The probable direct and indirect relationship of siRNA accumulation and up-regulated transcripts with the ToLCNDV tolerance mechanism is discussed.

Quantitative Trait Loci Mapping in Brassica rapa Revealed the Structural and Functional Conservation of Genetic Loci Governing Morphological and Yield Component Traits in the A, B, and C Subgenomes of Brassica Species

Abstract: Brassica rapa is an important crop species that produces vegetables, oilseed, and fodder. Although many studies reported quantitative trait loci (QTL) mapping, the genes governing most of its economically important traits are still unknown. In this study, we report QTL mapping for morphological and yield component traits in B. rapa and comparative map alignment between B. rapa, B. napus, B. juncea, and Arabidopsis thaliana to identify candidate genes and conserved QTL blocks between them. A total of 95 QTL were identified in different crucifer blocks of the B. rapa genome. Through synteny analysis with A. thaliana, B. rapa candidate genes and intronic and exonic single nucleotide polymorphisms in the parental lines were detected from whole genome resequenced data, a few of which were validated by mapping them to the QTL regions. Semi-quantitative reverse transcriptase PCR analysis showed differences in the expression levels of a few genes in parental lines. Comparative mapping identified five key major evolutionarily conserved crucifer blocks (R, J, F, E, and W) harbouring QTL for morphological and yield components traits between the A, B, and C subgenomes of B. rapa, B. juncea, and B. napus. The information of the identified candidate genes could be used for breeding B. rapa and other related Brassica species.

A Wavelet-based Neural Network Model to Predict Ambient Air Pollutants’ Concentration

Abstract: The present paper proposes a wavelet based recurrent neural network model to forecast one step ahead hourly, daily mean and daily maximum concentrations of ambient CO, NO2, NO, O3, SO2 and PM2.5 — the most prevalent air pollutants in urban atmosphere. The time series of each air pollutant has been decomposed into different time-scale components using maximum overlap wavelet transform (MODWT). These time-scale components were made to pass through Elman network. The number of nodes in the network was decided on the basis of the strength (power) of the corresponding input signals. The wavelet network model was then used to obtain one-step ahead forecasts for a period extending from January 2009 to June 2010. The model results for out of sample forecast are reasonably good in terms of model performance parameters such as mean absolute error (MAE), mean absolute percentage error (MAPE), root mean square error (RMSE), normalized mean absolute error (NMSE), index of agreement (IOA) and standard average error (SAE). The MAPE values for daily maximum concentrations of CO, NO2, NO, O3, SO2 and PM2.5 were found to be 9.5%, 17.37%, 21.20%, 13.79%, 17.77% and 11.94%, respectively, at ITO, Delhi, India. Bearing in mind that the forecasts are for daily maximum concentrations tested over a long validation period, the forecast performance of the model may be considered as reasonably good. The model results demonstrate that a judicious selection of wavelet network design may be employed successfully for air quality forecasting.

Controls on the major-ion chemistry of the Dokriani glacier meltwaters, Ganga basin, Garhwal Himalaya, India

Abstract: A detailed study of the major-ion chemistry of the Dokriani glacier meltwaters, feeding the Bhagirathi river, Ganga basin, Garhwal Himalaya, India, has been carried out to assess the role of active glaciers in the higher chemical-denudation rate (CDR) in this area. The CDR of the Dokriani glacier catchment is 321.6 t km - a - , higher than in other glacierized catchments of the world, indicating intense chemical erosion in the glacierized catchments of the Himalaya. The dominance of Ca 2+ , HCO 3 - and SO 4 2- in meltwaters throughout the 6 month (May-October) ablation period suggests that the chemical weathering is dominated by coupled reactions involving sulphide oxidation and carbonate dissolution. Good positive correlation between SO 4 2- and suspended-sediment concentration during July and August (r 2 = 0.72 and 0.67, respectively) suggests that the southwest monsoonal rainfall enhances the weathering of supraglacial moraine and contributes significant amounts of sulphate to the high meltwater discharges. The sulphate flux, as a proportion of combined (SO 4 2 + HCO 3 - ) flux, also increased from 45% at 2 m 3 s -1 to 63% at 10 m 3 s -1 .