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.

PIPEMicroDB: microsatellite database and primer generation tool for pigeonpea genome.

Abstract: Molecular markers play a significant role for crop improvement in desirable characteristics, such as high yield, resistance to disease and others that will benefit the crop in long term. Pigeonpea (Cajanus cajan L.) is the recently sequenced legume by global consortium led by ICRISAT (Hyderabad, India) and been analysed for gene prediction, synteny maps, markers, etc. We present PIgeonPEa Microsatellite DataBase (PIPEMicroDB) with an automated primer designing tool for pigeonpea genome, based on chromosome wise as well as location wise search of primers. Total of 123 387 Short Tandem Repeats (STRs) were extracted from pigeonpea genome, available in public domain using MIcroSAtellite tool (MISA). The database is an online relational database based on ‘three-tier architecture’ that catalogues information of microsatellites in MySQL and user-friendly interface is developed using PHP. Search for STRs may be customized by limiting their location on chromosome as well as number of markers in that range. This is a novel approach and is not been implemented in any of the existing marker database. This database has been further appended with Primer3 for primer designing of selected markers with left and right flankings of size up to 500 bp. This will enable researchers to select markers of choice at desired interval over the chromosome. Furthermore, one can use individual STRs of a targeted region over chromosome to narrow down location of gene of interest or linked Quantitative Trait Loci (QTLs). Although it is an in silico approach, markers’ search based on characteristics and location of STRs is expected to be beneficial for researchers. Database URL: http://cabindb.iasri.res.in/pigeonpea/

Small Area Estimation for Zero-Inflated Data

Abstract: The commonly used method of small area estimation (SAE) under a linear mixed model may not be efficient if data contain substantial proportion of zeros than would be expected under standard model assumptions (hereafter zero-inflated data). The authors discuss the SAE for zero-inflated data under a two-part random effects model that account for excess zeros in the data. Empirical results show that proposed method for SAE works well and produces an efficient set of small area estimates. An application to real survey data from the National Sample Survey Office of India demonstrates the satisfactory performance of the method. The authors describe a parametric bootstrap method to estimate the mean squared error (MSE) of the proposed estimator of small areas. The bootstrap estimates of the MSE are compared to the true MSE in simulation study.

Dioxin-like and non-dioxin-like PCBs differentially regulate the hepatic proteome and modify diet-induced nonalcoholic fatty liver disease severity.

Abstract: Polychlorinated biphenyls (PCBs) are persistent organic pollutants associated with metabolic disruption and non-alcoholic fatty liver disease (NAFLD). Based on their ability to activate the aryl hydrocarbon receptor (AhR), PCBs are subdivided into two classes: dioxin-like (DL) and non-dioxin-like (NDL) PCBs. Previously, we demonstrated that NDL PCBs compromised the liver to promote more severe diet-induced NAFLD. Here, the hepatic effects and potential mechanisms (by untargeted liver proteomics) of DL PCBs, NDL PCBs or co-exposure to both in diet-induced NAFLD are investigated. Male C57Bl/6 mice were fed a 42% fat diet and exposed to vehicle control; Aroclor1260 (20 mg/kg, NDL PCB mixture); PCB126 (20 μg/kg, DL PCB congener); or a mixture of Aroclor1260 (20 mg/kg)+PCB126 (20 μg/kg) for 12 weeks. Each exposure was associated with a distinct hepatic proteome. Phenotypic and proteomic analyses revealed increased hepatic inflammation and phosphoprotein signaling disruption by Aroclor1260. PCB126 decreased hepatic inflammation and fibrosis at the molecular level; while altering cytoskeletal remodeling, metal homeostasis, and intermediary/xenobiotic metabolism. PCB126 attenuated Aroclor1260-induced hepatic inflammation but increased hepatic free fatty acids in the co-exposure group. Aroclor1260+PCB126 exposure was strongly associated with multiple epigenetic processes, and these could potentially explain the observed non-additive effects of the exposures on the hepatic proteome. Taken together, the results demonstrated that PCB exposures differentially regulated the hepatic proteome and the histologic severity of diet-induced NAFLD. Future research is warranted to determine the AhR-dependence of the observed effects including metal homeostasis and the epigenetic regulation of gene expression.

Soil temperature prediction from air temperature for alluvial soils in lower Indo-Gangetic plain

Abstract: Abstract Soil temperature is an important factor in biogeochemical processes. On-site monitoring of soil temperature is limited in spatiotemporal scale as compared to air temperature data inventories due to various management difficulties. Therefore, empirical models were developed by taking 30-year long-term (1985-2014) air and soil temperature data for prediction of soil temperatures at three depths (5, 15, 30 cm) in morning (0636 Indian standard time) and afternoon (1336 Indian standard time) for alluvial soils in lower Indo-Gangetic plain. At 5 cm depth, power and exponential regression models were best fitted for daily data in morning and afternoon, respectively, but it was reverse at 15 cm. However, at 30 cm, exponential models were best fitted for both the times. Regression analysis revealed that in morning for all three depths and in afternoon for 30 cm depth, soil temperatures (daily, weekly, and monthly) could be predicted more efficiently with the help of corresponding mean air temperature than that of maximum and minimum. However, in afternoon, prediction of soil temperature at 5 and 15 cm depths were more precised for all the time intervals when maximum air temperature was used, except for weekly soil temperature at 15 cm, where the use of mean air temperature gave better prediction.