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Annual Report 2011-2012 - Nabi.res.in

Annual Report 2011-2012 - Nabi.res.in

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NATIONAL AGRI-FOOD BIOTECHNOLOGY INSTITUTE5.1.2 Wheat genechip microarray data m<strong>in</strong><strong>in</strong>g out of the 61127 probe sets of wheat.for identification of SFPs <strong>in</strong> Indian cultivars and Optimization of script is under prog<strong>res</strong>s.annotation of hypothetical prote<strong>in</strong>sIntroduction:5.1.3 Development of small RNA analysispipel<strong>in</strong>eSNPs and <strong>in</strong>sertion or deletions of one or morenucleotides (<strong>in</strong>dels) are DNA polymorphisms thatcan affect hybridization of DNA or cRNA to aprobe on an array. The Affymetrix Gene Chiparrays are suitable to detect such variationsbecause each gene is rep<strong>res</strong>ented by a set of eleven25-bp probes that are sensitive to target mismatchow<strong>in</strong>g to their short sequence. A target sequencethat matches the sequence of a probe b<strong>in</strong>ds withmuch greater aff<strong>in</strong>ity than one with a mismatchsequence. The <strong>res</strong>ult<strong>in</strong>g difference <strong>in</strong>hybridization <strong>in</strong>tensity between two genotypes foran <strong>in</strong>dividual probe is called a SFP, where a featurerefers to a probe <strong>in</strong> the array. A SFP may be causedby a SNP, a multiple nucleotide polymorphism, oran <strong>in</strong>del.Research Objective:To predict SFPs <strong>in</strong> the genomes of the follow<strong>in</strong>gwheat varieties: C-306, LOK1, Sonalika andWH291, us<strong>in</strong>g microarray data.Research <strong>in</strong> Prog<strong>res</strong>s:1. An algorithm was written for predict<strong>in</strong>gSFPs us<strong>in</strong>g the normalized exp<strong>res</strong>sion signalvalues of the four wheat varieties.2. Standard deviation values were computedus<strong>in</strong>g the normalized signal <strong>in</strong>tensity valuesof perfect match probes of a probeset for allthe four wheat varieties 7 DAA,14 DAA and 28 DAA.Introduction:miRNAs are small and endogenous RNAs thatregulate endogenous genes or gene exp<strong>res</strong>sion.miRNAs are important for implement<strong>in</strong>gdevelopmental programs <strong>in</strong> animals and plants.Our <strong>res</strong>earch focus is on plant miRNA predictionand its target prediction (miRNA). In plants, these~18-24 nt RNAs are processed from stem-loopregions of long primary transcripts by a dicer-likeenzyme and are loaded <strong>in</strong>to silenc<strong>in</strong>g complexes,where they generally direct cleavage ofcomplementary mRNAs. NABI has <strong>in</strong>itiatedexperiments to generate small RNA sequencesus<strong>in</strong>g Illum<strong>in</strong>a platform for RNA isolated fromcontrast<strong>in</strong>g samples of wheat, custard apple, litchiand mango to understand small RNA regulationand identify novel regulatory small RNA. Longterm goal under this component is to reconstructgene regulatory networks us<strong>in</strong>g multi-dimensiondata. Small RNA prediction and its targetprediction will be done us<strong>in</strong>g <strong>in</strong>-house developedpipel<strong>in</strong>e of open source prediction tools andcustomized scripts. Bench mark<strong>in</strong>g of differentsoftwa<strong>res</strong> (<strong>in</strong> the pipel<strong>in</strong>e) is <strong>in</strong> prog<strong>res</strong>s us<strong>in</strong>gdatasets available <strong>in</strong> public doma<strong>in</strong>.Research Objectives:lBench-mark<strong>in</strong>g of miRNA prediction andmiRNA-target prediction tools.3.l Development of small RNA analysisFour average standard deviation values werePipel<strong>in</strong>e.used as reference values to predict SFP. SFPis predicted if the standard deviation valuesl Development of <strong>in</strong>-house small RNAof a probe of a probeset are less than or equal database.to the m<strong>in</strong>imum of the four average standarddeviation values.l Comparative analysis of small RNA4. Python script was written based on the aboveregulation.written statistical logic for predict<strong>in</strong>g SFPs l Reconstruction of gene regulatory networks.39

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