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Work presentation. Gaurav Moghe Feb 4 th , 2008 – March 17 th , 2008. Projects. Divergence between DDF1 and DDF2 Expression differences between A.thaliana and A.lyrata under JA-induced stress Novel coding regions in A. thaliana Amanitus-related toxins in other fungal genomes.
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Work presentation Gaurav Moghe Feb 4th , 2008 – March 17th, 2008
Projects • Divergence between DDF1 and DDF2 • Expression differences between A.thaliana and A.lyrata under JA-induced stress • Novel coding regions in A. thaliana • Amanitus-related toxins in other fungal genomes
1. Divergence between DDF1 and DDF2 Objective: To find protein-level differences between DDF1 and DDF2 using translational fusions Subobjective: • Verify transformants for GUS marker -- GUS Staining -- Homo/Heterozygosity using GUS-specific primers
Strategy: Translational fusions 10 lines DDF1 GUS Endogenous promoter DDF2 GUS 1 line Endogenous promoter Spatial and temporal differentiation of expression in Arabidopsis • But, • Existing lines from older A. thaliana strains. • Moving everything to the newer Col0 strains.
GUS Staining results • Tried GUS staining from leaves, flowers, roots and first inter-node • No GUS activity detected • Progeny of transformants not differentiable by Hyg resistance phenotype
Future plans 1) New Col0 strains (DDF1-GUS) put on soil 2) Perform GUS staining with new Col0 strains under salt-stress from roots and inter-node 3) Verify homo / heterozygosity using GUS-specific primers
ChIP-Sequencing part • 35S-cMyc-DDF1/2 construct (1 probable plant) • 35S-DDF1/2-GFP construct Transformant should show over-expression phenotype, but that was not observed for GFP construct. So, will have to be re-done.
2. JA-induced stress expression Extract RNA using RNAeasy Solexa sequencing qRT-PCR Analysis
DNA contamination • The extracted RNA samples (200ng) were PCR-amplified using GoTaq with: • actin_6 (flanks an intron) • DDF2 primers for 40X and 32X cycles. • Both the reactions showed significant presence of DNA (~20ng after amplification)
DNA contamination: options • The SuperArray RT2 First strand kit (Problem: Two-step RTPCR. No kit mentioned for Eppendorf Realplex machine) • Design primers flanking the longest introns • If possible, keep a smaller extension time(?) (Problem: Can affect RNA amplification) • Keep RT(-) control during qRT-PCR (Problem: What is the best way to subtract effect of DNA?) • Re-do the extraction
3. Novel coding regions in A.thaliana Two directions of study Gene predictors RNA genes • Augustus • GlimmerM • GeneID • TwinScan • EuGene • CONTRAST • SNAP BioPerl installation issue For some reason, not accepting Chr4 and Chr 5 Whole genome alignments
Predicting existence of yet un-annotated RNA genes • Question: Are there any regions in the genome that: • Are not known proteins/RNA? • Conserved across phylogeny? Are such regions: • RNA? • Protein?
RNA genes: Strategy Download A.thaliana PUTs from PlantGDB (best alternative to FLcDNA) RFAM database of known/predicted RNA molecules BLASTx against UniProt (UniRef90) (1) Filter (1) using (2) distribution BLASTx against UniProt (UniRef90) (2) Retain non-matching and not significantly matching PUTs PUTs not known to be proteins Discard significant matches
RNA genes: Strategy PUTs not known to be proteins 10000 randomly generated PUTs for pre-selected size classes of the original PUTs BLASTn against RFAM (1) Filter (1) using (2) distribution BLASTn against RFAM (2) Retain non-matching and not significantly matching PUTs PUTs not known to be proteins or RNA Discard significant matches
RNA genes: Strategy PUTs not known to be proteins or RNA Are these PUTs mapped to A. thaliana genome? Yes BLAST against PUTs from different plants strategically placed in phylogeny Conserved regions not yet annotated • RNA prediction softwares • RNAZ • QRNA • ddbRNA • EvoFold • MSARI Find conserved PUTs
4. Amanita toxin project (Walton lab) • Multiple sequence alignment of several toxin genes from two fungal genera – Amanita and Galerina • Sequenced fungal genomes • tBLASTn with relaxed parameters does not give any significant hits
Use of Hidden Markov Model (HMM) to generate a PWM for MSA of toxins Ama-like toxins MSA M ARLP PC E HMM HMM Scan 6-frame translated fungal genomes Scan 6-frame translated fungal genomes Hits of very low e-value (100-1000), but some degree of relevant sequence similarity