This section outlines efficient stepwise procedures for analyzing the matrix attachment regions (MARs), translation initiation sites (TIS), signal peptide (SP) sequences, gene optimization, and transformation systems. The strategies initially include data mining (DNA, RNA, and protein for MARs, TIS, and SP, respectively) and screening for the validated data. The in silico process for MARs exploration comprises motif search and comparison in databases, correlation analysis, design, and evaluation of an artificial MAR sequence. Investigation on TIS is carried out based on the statistical evaluation of the nucleotide occurrence variation around the ATG (translation initiation) site. Various programs are available to predict signal peptide sequences throughout the genome, among which SignalP is preferred in terms of performance comparing other similar programs. For gene optimization, in addition to codon preference, the mRNA secondary structures are also evaluated. Finally, the transformation procedures and efficiency of different methods are discussed.
KeywordsS/MARs TIS SP Gene optimization
- 4.Kadkhodaei S, Nekouei MK, Shahnazari M, Etminani H, Imani A, Ghaderi-Zefrehei M, Elahy M, Ariff AB (2011) Molecular tagging of agronomic traits using simple sequence repeats: Informative markers for almond (Prunus dulcis) molecular breeding. Aust J Crop Sci 5:1199–1209Google Scholar
- 7.R Core Team (2014) R: a language and environment for statistical computing. R Found Stat Comput Vienna, Austria. URL http://www.R-project.org/