Zhang et al. BMC Genomics 2011, 12:63 http://www.biomedcentral.com/1471-2164/12/63 precocious trifoliate orange trifoliate orange were planted in 20-cm pots containing a potting mix of a commercial medium and perlite at a ratio of 3:1. The juvenile potted seedlings were then transplanted and grown under field conditions. These juvenile trees were watered regularly with a nutrient solution. The terminal bud and the five following buds (the major node posi- tion for flower formation) from spring flushes of these MT and WT trees were collected after self-pruning, sepal primordia arise, petal primordia arise, stamen pri- mordia arise, pistil primordia arise, and full-developed floral bud, respectively. All materials were collected from three individual plants and immediately frozen in liquid nitrogen and stored at -80°C until analyzed. Total RNA was extracted according to a previous pro- tocol [23]. A 1.2% agarose gel, stained with ethidium bromide, was run to preliminarily indicate the integrity of the RNA. All RNA samples were quantified and examined for protein contamination (A260/280) and reagent contamination (A260/230) by a Nanodrop ND 1000 spectrophotometer. In addition, the RIN (RNA integrity number) determined by the Agilent Technolo- gies 2100 Bioanalyzer was greater than 8.5 for all samples. Massively parallel signature sequencing The materials used for MPSS analyses were the term- inal bud and the five following buds from MT and WT spring shoots after self-pruning, which occurs in mid-April (our previous results indicated that self- pruning is the critical stage for floral differentiation). Twenty micrograms of total RNA were sent to Beijing Genomics Institute (Shenzhen, China) where the libraries were produced and sequenced using Illumi- na’s Genome Analyzer (Solexa). The MPSS was car- ried out essentially as in previous studies [29,66], with modifications from Long SAGE [67]. Briefly, cDNA with polyA/T tail was prepared and digested with DpnII restriction enzyme. An adaptor with an MmeI recognition site was ligated to the 50-end, followed by MmeI digestion that cut 21-22 bases downstream. This 21-22 base signature from each transcript was subsequently cloned by a unique adaptor and loaded to a microbead. This MPSS profiling process sampled 1-2 million sequenced transcripts per library on microbeads. Sequenced tags were generated by serial cutting and ligation of decoding adaptors. Sequencing runs were done by using two different cleavage steps, which are two different four-nucleotide sequencing frames offset by two bases (two-step) or three bases (three-step) [29]. The abundance of each signature was normalized to one million (transcripts per million, TPM) for the purpose of making comparisons between samples. Page 17 of 20 MPSS data analyses To remove reads that might have arisen from errors in the MPSS procedure, two filters were applied to the derived reads [30]. The first, the “reliability filter,” removed low quality reads containing ambiguous nucleotides or adaptor sequences. The second, the “sig- nificance filter,” was intended to remove reads that were consistently present at background levels, excluding sig- natures lower than 3 TPM in both libraries according to the criteria described by Meyers et al. [30]. To link the expressed signatures to known genes from citrus, the unigene dataset from TIGR gene index data- base and Harvest database were combined to create a reference gene dataset. The signatures produced in silico were stored in the reference read database, through which the expressed MPSS signatures could be mapped on the corresponding EST contigs and singletons based on matches between MPSS signatures and in silico reads, as described previously [31]. The significance level of the differences of signature frequency and tran- script abundance between the two libraries was analyzed using the Z-score method according to Kal et al. [34]. Functional assignments of differentially expressed genes To assign putative functions to differentially expressed genes between MT and WT, annot8r program was run locally to BLAST against a reference database that stores UniProt entries, their associated Gene Ontology (GO), Enzyme Commission (EC), and Kyoto Encyclopaedia of Genes and Genomes (KEGG) annotation [56]. The GO categorization results were expressed as three indepen- dent hierarchies for biological process, cellular compo- nent, and molecular function [57]. The biological interpretation of the differentially expressed genes was further completed by assigning them to metabolic path- ways using KEGG [58]. For the identification of pathways significantly affected by the mutation, we focused on the metabolite pathways with at least three affiliated genes. Real-time quantitative RT-PCR verification Thirty genes were chosen for confirmation by real-time quantitative RT-PCR with SYBR green I chemistry (QIAGEN, Germany). Primers for these genes were designed with the Primer Express software (PE Applied Biosystems, USA) and tested to ensure amplification of single discrete bands with no primer-dimers. Product size was about 180 bp. Total RNA (3 mg) was treated with 3 U of DNase (Promega, USA) and then used in first-strand synthesis with an oligo (dT) primer (20-mer) and reverse transcriptase according to the manufac- turer’s instructions. For real-time PCR, an amount of cDNA corresponding to 25 ng of input RNA was used in each reaction. Reactions were performed with the SYBR Green PCR Master Mix and analyzed in the ABI