What The Heck Is Going On With The AUY-922

Figure 1 Schematic representation of the functional analysis pipeline for ginger EST pre-processing and database construction Functional analysis: Blast2GO (B2GO), [19] comprehensive software for sequence analysis was used for the functional annotation of ginger ESTs. Putative functions were analyzed by performing blastx against non-redundant protein sequence database. For further perception of the functional classification, the EST contigs were submitted to Gene Ontology analysis (GO). Cellular component, biological process, and molecular function were classified for these contigs. Unigenes were further subjected to pathway analysis using KEGG. InterPro Scan [20] embedded with B2GO was utilized to obtain the protein AUY 922 domain information for the putative sequences. SSR detection: Simple Sequence Repeats (SSRs) analysis on contigs of ginger was performed using SSR Finder from GRAMENE (ftp://ftp.gramene.org/ pub/gramene/software/scripts/ ssr.pl). The parameters were set for detection of di-, tri-, tetra-, penta-, and hexa-nucleotide SCH 900776 price units with a minimum of six, five, four, four and four repeats respectively [21]. Primer pairs for each detected SSR were designed using Eprimer3 from EMBOSS software packages (http://emboss.sourceforge.net/). Parameters used to design flanking primers were primer length 18 to 24 nt with an optimum of 20 nt, annealing temperature with optimum 60��C, GC content ranging from 40 to 60% with an optimum 50% [22]. Identification of novel miRNAs: Raw EST sequences from Zingiber officinale and EST contigs obtained after data preprocessing were combined to form the subject dataset. All known Viridiplantae miRNAs from the publicly available EST database, miRBase (Release 20: June 2013, http://www.mirbase.org/) B3GAT3 [23] was used as a reference set and performed homology searches using blastn. Blast parameter settings were as follows: expect value - 0.01; the maximum number of alignments -100. Python script was developed for the identification of miRNAs. EST sequences with n/n, n-1/n and n-2/n nucleotide mismatches were identified and retained for further analysis. A 60-400 nt sliding window was chosen to predict the secondary structure of premiRNAs using mfold algorithm (~14000 bp for each EST). If the length of EST sequence is