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.

Epilepsy in children with cerebral palsy.

Abstract: This article deals with the clinical profile of children with cerebral palsy and epilepsy, and to study the clinical predictors of response to anti-epileptic drugs. It is a prospective hospital based follow-up study. All the children who presented with cerebral palsy and history of seizure (other than neonatal seizures) over a period of one year were included. Seizures were classified according to ILAE classification. An EEG was obtained in all cases. Neuroimaging was done in all patients. Eighty-five patients were studied and followed for minimum of 12 months. Perinatal factors accounted for 62 (72.3%) cases. The motor deficits seen were quadriparesis (n = 64), hemiplegia (n = 12) and diplegia(n = 9). Associated mental retardation was seen in 80.9% patients with quadriparesis. A predominance of generalised epilepsy was seen with generalised tonic clonic seizures (32.9%) followed by myoclonic seizures(30.6%)and localisation related epilepsy (24.7%). The patients with quadriparesis were more likely to have generalised epilepsy and 52.4% of them required two or more anti-epileptic drugs for control of seizures. Patients with hemiplegia had localisation related epilepsy in 83.3% of cases. On multivariate analysis presence of quadriparesis, microcephaly, mental retardation and myoclonic epilesy were found to predict the poor response to AED. Epilepsy in patients with cerebral palsy is of severe nature and difficult to control. Presence of quadriparesis, mental retardation and myoclonic seizures was predictive of poor response to anti-epileptic drugs.

Identification of QTLs/Defense Genes Effective at Seedling Stage Against Prevailing Races of Wheat Stripe Rust in India.

Abstract: Resistance in modern wheat cultivars for stripe rust is not long lasting due to narrow genetic base and periodical evolution of new pathogenic races. Though, nearly 83 Yr genes conferring resistance to stripe rust have been cataloged so far, hardly few of them have been mapped and utilized in breeding programs. Characterization of wheat germplasm for novel sources of resistance and their incorporation into elite cultivars is required to achieve durable resistance and thus, to minimize the yield losses. Here, a genome-wide association study (GWAS) was performed on a set of 391 germplasm lines with the aim to identify quantitative trait loci (QTL) using 35K Axiom® array. Phenotypic evaluation disease severity against four stripe rust pathotypes i.e., 46S119, 110S119, 238S119 and 47S103 (T) at the seedling stage under glass house providing optimal conditions was carried out consecutively for two years (2018 and 2019 winter season). Association study revealed that a total of 40 QTLs were significantly associated with seedling-plant resistance to stripe rust. Out of these, 20 QTLs were found to be closely linked with previously reported yellow rust resistance genes/QTLs on chromosomes 1B, 2B, 5B and 6B while 20 novel QTLs were mapped on chromosomes 2D, 3A, 3D, 5A and 7D. These 20 novel QTLs identified in the present study might play a key role in marker-assisted breeding for developing stripe rust resistant wheat cultivars.

A statistical approach for 5′ splice site prediction using short sequence motifs and without encoding sequence data

Abstract: Background: Most of the approaches for splice site prediction are based on machine learning techniques. Though, these approaches provide high prediction accuracy, the window lengths used are longer in size. Hence, these approaches may not be suitable to predict the novel splice variants using the short sequence reads generated from next generation sequencing technologies. Further, machine learning techniques require numerically encoded data and produce different accuracy with different encoding procedures. Therefore, splice site prediction with short sequence motifs and without encoding sequence data became a motivation for the present study. Results: An approach for finding association among nucleotide bases in the splice site motifs is developed and used further to determine the appropriate window size. Besides, an approach for prediction of donor splice sites using sum of absolute error criterion has also been proposed. The proposed approach has been compared with commonly used approaches i.e., Maximum Entropy Modeling (MEM), Maximal Dependency Decomposition (MDD), Weighted Matrix Method (WMM) and Markov Model of first order (MM1) and was found to perform equally with MEM and MDD and better than WMM and MM1 in terms of prediction accuracy. Conclusions: The proposed prediction approach can be used in the prediction of donor splice sites with higher accuracy using short sequence motifs and hence can be used as a complementary method to the existing approaches. Based on the proposed methodology, a web server was also developed for easy prediction of donor splice sites by users and is available at http://cabgrid.res.in:8080/sspred.

RiceMetaSysB: a database of blast and bacterial blight responsive genes in rice and its utilization in identifying key blast-resistant WRKY genes.

Abstract: Nearly two decades of revolution in the area of genomics serves as the basis of present-day molecular breeding in major food crops such as rice. Here we report an open source database on two major biotic stresses of rice, named RiceMetaSysB, which provides detailed information about rice blast and bacterial blight (BB) responsive genes (RGs). Meta-analysis of microarray data from different blast- and BB-related experiments across 241 and 186 samples identified 15135 unique genes for blast and 7475 for BB. A total of 9365 and 5375 simple sequence repeats (SSRs) in blast and BB RGs were identified for marker development. Retrieval of candidate genes using different search options like genotypes, tissue, developmental stage of the host, strain, hours/days post-inoculation, physical position and SSR marker information is facilitated in the database. Search options like 'common genes among varieties' and 'strains' have been enabled to identify robust candidate genes. A 2D representation of the data can be used to compare expression profiles across genes, genotypes and strains. To demonstrate the utility of this database, we queried for blast-responsive WRKY genes (fold change ≥5) using their gene IDs. The structural variations in the 12 WRKY genes so identified and their promoter regions were explored in two rice genotypes contrasting for their reaction to blast infection. Expression analysis of these genes in panicle tissue infected with a virulent and an avirulent strain of Magnaporthe oryzae could identify WRKY7, WRKY58, WRKY62, WRKY64 and WRKY76 as potential candidate genes for resistance to panicle blast, as they showed higher expression only in the resistant genotype against the virulent strain. Thus, we demonstrated that RiceMetaSysB can play an important role in providing robust candidate genes for rice blast and BB.

SSH Analysis of Endosperm Transcripts and Characterization of Heat Stress Regulated Expressed Sequence Tags in Bread Wheat.

Abstract: Heat stress is one of the major problems in agriculturally important cereal crops, especially wheat. Here, we have constructed a subtracted cDNA library from the endosperm of HS-treated (42°C for 2 h) wheat cv. HD2985 by suppression subtractive hybridization (SSH). We identified ~550 recombinant clones ranging from 200 to 500 bp with an average size of 300 bp. Sanger’s sequencing was performed with 205 positive clones to generate the differentially expressed sequence tags (ESTs). Most of the ESTs were observed to be localized on the long arm of chromosome 2A and associated with heat stress tolerance and metabolic pathways. Identified ESTs were BLAST search using Ensemble, TriFLD and TIGR databases and the predicted CDS were translated and aligned with the protein sequences available in pfam and InterProScan 5 databases to predict the differentially expressed proteins (DEPs). We observed eight different types of post-translational modifications (PTMs) in the DEPs corresponds to the cloned ESTs—147 sites with phosphorylation, 21 sites with sumoylation, 237 with palmitoylation, 96 sites with S-nitrosylation, 3066 calpain cleavage sites, and 103 tyrosine nitration sites, predicted to sense the heat stress and regulate the expression of stress genes. Twelve DEPs were observed to have transmembrane helixes (TMH) in their structure, predicted to play the role of sensors of HS. Quantitative Real-Time PCR of randomly selected ESTs showed very high relative expression of HSP17 under HS; up-regulation was observed more in wheat cv. HD2985 (thermotolerant), as compared to HD2329 (thermosusceptible) during grain-filling. The abundance of transcripts was further validated through northern blot analysis. The ESTs and their corresponding DEPs can be used as molecular marker for screening or targeted precision breeding program. PTMs identified in the DEPs can be used to elucidate the thermotolerance mechanism of wheat – a novel step towards the development of ‘climate-smart’ wheat.