Indian Agricultural Statistics Research Institute

About: Indian Agricultural Statistics Research Institute is a facility organization based out in New Delhi, India. It is known for research contribution in the topics: Population & Small area estimation. The organization has 454 authors who have published 870 publications receiving 7987 citations.

Classification of Cereal Proteins Related to Abiotic Stress Based on their Physicochemical Properties Using Support Vector Machine

Abstract: Abiotic stress factors severely limit plant growth and development as well as crop yield. There is a great need to develop understanding of plant physiological responses to abiotic stresses in order to improve crop productivity through crop improvement programmes. Proteins play a central role in plant adaptations under stress and hence their identification is important to the biologist. Identification of such proteins by wet lab experimentation is sometimes expensive and timeconsuming. In such a situation, in silico approaches can be used to narrow down this search. In this study, classification of cereal proteins subjected to four different stresses, namely, extreme temperature, drought, salt and abscisic acid (ABA) was undertaken. Classification models were built using support vector machine (SVM) to predict the function of proteins under these abiotic stresses on the basis of 34 physicochemical features extracted from the protein sequence. Specific features of the protein sequence that are highly correlated with certain protein functions were selected by stepwise logistic regression, a feature selection method. SVM was trained using different kernel functions and cross-validated using 10-fold crossvalidation technique. Prediction precision was assessed through different measures such as sensitivity, specificity and accuracy. The accuracy of protein function prediction using SVM with different kernel functions ranges from 60% to 100%.

Promoter sequence interaction and structure based multi-targeted (redox regulatory genes) molecular docking analysis of vitamin E and curcumin in T4 induced oxidative stress model using H9C2 cardiac cell line.

Abstract: A positive association between oxidative stress and hyper-thyroid conditions is well established. Vitamin E (VIT-E) and curcumin (CRM) are considered as potent antioxidant small molecules. Nuclear factor erythroid 2-related factor 2(NRF-2) is known to bind with antioxidant response element and subsequently activate expression of antioxidant enzymes. However, the activation of NRF-2 depends on removal of its regulator Kelch-like ECH-associated protein 1(NRF-2). In the current study, an attempt is made to demonstrate whether effects of VIT-E and CRM are due to direct interaction with the target proteins (i.e. NRF-2, NRF-2, SOD, catalase and LDH) or by possible interaction with the flanking region of their promoters by in silico analysis. Further, these results were corroborated by pretreatment of H9C2 cells (1 x 106 cells per mL of media) with VIT-E (50 μM) and/or CRM (20 μM) for 24 h followed by induction of oxidative stress via T4 (100 nm) administration and assaying the active oxygen metabolism. Discriminant function analyses (DFA) indicated that T4 has a definite role in increasing oxidative stress as evidenced by induction of ROS generation, increase in mitochondrial membrane potential and elevated lipid peroxidation (LPx). Pretreatment with the two antioxidants have ameliorative effects more so when given in combination. The decline in biological activities of the principal antioxidant enzymes SOD and CAT with respect to T4 treatment and its restoration in antioxidant pretreated group further validated our in silico data. Communicated by Ramaswamy H. Sarma.

District-Level Crop Yield Estimation Using Calibration Approach

Abstract: Estimation of major crop yield rates at the district level using calibration estimation technique is reported here when auxiliary information is available at the unit level only for the selected villages within each district and when the sampling design under consideration is two-stage equal probability without replacement. An estimator was developed for the complex sampling design under consideration using the calibration approach. Through evaluation using real data collected from a pilot survey, we found that the proposed calibration estimator performs better than the usual design-based Horvitz-Thompson estimator under two-stage sampling design.

Genome-wide analysis and identification of abiotic stress responsive transcription factor family genes and miRNAs in bread wheat (Triticumaestivum L.): Genomic study of bread wheat

Abstract: Transcription factors (TFs) act as master regulators that directly bind to their respective distinct cis-regulatory elements and activate the expression of many downstream target genes (regulon), and thus play a key regulatory role in plant development and stress tolerance. TF families such as AP2/EREBP, AREB/ABF, bHLH, bZIP, C2H2, C3HIS, HB, DREB1/CBF, HSF, MADS, MYB, MYC, NAC, WRKY, etc., were known to regulate stress responses of plants and were relatively well studied in rice and Arabidopsis. Bread wheat (Triticumaestivum L) draft genome is recently released and is available in Ensembl Plants database. We used known rice TFs and build Hidden Markov Model (HMM) profiles for individual TF protein families. These Profile HMMs in turn were used to search respective wheat homologs. SMART tool was used for domain identification. Our analysis showed that the wheat genome consists of 201, 166, 265, 182, 200, 102, 200, 274, 54, 125, 315, 226 and 199 genes of AP2/EREBP, AREB/ABF, bHLH, bZIP, C2H2, C3HIS, HB, HIS, HSF, MADS, MYB, NAC and WRKY families, respectively. Genome-wide analysis of miRNAs from wheat genome resulted in identification of 4533 miRNAs from wheat. Further, miRNAs targeting abiotic stress responsive TFs is identified. The genome distribution of abiotic stress responsive TFs and miRNAs strongly supports the hypothesis that genome-wide and tandem duplication contributed to the expansion of these gene families in wheat.

Improved chain-ratio type estimator for population total in double sampling

Abstract: Chain-ratio estimators are often used to improve the efficiency of the estimation of the population total or the mean using two auxiliary variables, available in two different phases. An improved c...