Figure 2. Monitoring the process of MgC-GEP. (A) Detection of the PCR products digested. Lane 1 was the PCR products without digestion. Lane 2 was the PCR products digested with BamHI and HindIII. The RT-PCR products digested and undigested were separated by 3% agarose gel electrophoresis and stained with ethidium bromide. Marker (M) was the pUC18 DNA/MspI (TIANGEN). (B) The digested products were ligated to produce concatemers with T4 DNA ligase. The concatemers were analyzed by using 1.5% agarose gel and stained with ethidium bromide. Maker (M) was the MIII (DingGuo). (C) Insert size of 15 clones was estimated by PCR analysis. The PCR products were analyzed by using 1% agarose gel and stained with ethidium bromide. Lanes 1 to 15 were the different clones selected randomly. Marker (M) was the MIII (DingGuo). doi:10.1371/journal.pone.0015711.g002 weak acid in S. cerevisiae using the MgC-GEP and real-time RT- PCR, respectively. Additionally, we have successfully detected the transcription of 8 genes of Toll pathway of Locusta migratoria manilensis in eight different tissues at six time points using MgC- GEP (unpublished data). It demonstrated that MgC-GEP could exactly determine the transcript levels of a moderate number of genes at once effectively. In MgC-GEP, two initial steps were performed to synthesize cDNA using specific primers containing universal tags with specific digestion sites at both termini. The universal tags, containing the specific digestion sites, will facilitate the formation of concater- mers. It offers another advantage, namely, the simplification of the subsequent step by making it possible to analyze the fragments by polyacrylamide gel electrophoresis or agarose gel electrophoresis. Importantly, MgC-GEP is based on sequencing technique and can be freely applied in most laboratories without the acquisition of specific equipments. Multiple primer design is a very important step in MgC-GEP. First of all, the calculated primer melting temperature (Tm) and the size of PCR products should be similar so that all primers anneal at same temperatures during the PCR temperature cycling for better balance between PCR products in a multiplex reaction Multigene Expression Profiling [41]. Moreover, high quality primers are essential for successful multiplex amplification reactions. During 3–28 cycles in the amplification, the universal primers are more competitive than the chimeric primers due to their higher abundance. At this time, different genes are amplified with the same universal primer pairs. Therefore, the chimeric primers and universal primers could lead to the same efficiency for each amplicon. When choosing a method for quantifying gene expression, there are several basic considerations, including specificity, throughput, sensitivity, cost and data analysis. Like SAGE and SuperSAGE, MgC-GEP is based on the sequential analysis of short cDNA sequence tags [20,21]. Each tag is derived from a defined position within a transcript. For specificity, the size (.60 bp) of the tags is long enough to be identified as the corresponding gene and the frequency of each tag numbered provides an accurate measurement of its expression level. Closely related gene sequences could be discriminated through precise primer designing and sequencing in MgC-GEP. Specifically, this method could allow the accurate determination of the expression levels of multiple transcripts that could lead to the false positive of an expression differential by hybridization due to the high identity at nucleotide level. For sensitivity, it is possible to detect poorly expressed genes with high sensitivity using MgC-GEP since it is a PCR-based technique. For throughput, the transcript levels of at least 20 genes could be monitored at once using MgC- GEP. It was more practical to monitor the transcript levels of 10– 50 genes under the various conditions or at different times than the real-time RT-PCR, DNA microarray and SAGE. For real- time multiplex RT-PCR, if one template is much more abundant than the other templates in the same reaction tube, the reaction components will be depleted before the lower-abundance targets have amplified sufficiently to be detected [23]. For DNA microarray and SAGE, though thousands of genes could be determined, the large cost of multiple samples may be the main constraint [18]. For example, detecting the expression profiling of 10–50 genes in kinetics studies or comparing the effects of a large number of drugs is costly. The GeXP method is a good choice for multigene expression profiling of multiple samples, but the necessary equipments such as a fluorescence scanner (detector) and a capillary electrophoresis machine are required to generate the data [38,39]. This is inconvenient for laboratories that do not possess this equipment. MgC-GEP can be applied in most laboratories and done readily without additional cost and equipment. Another advantage is in data analysis, MgC-GEP can use Blast analysis to detect and count tags from sequence files, thus can analyze the experimental data without the necessity of professional software. Although there are distinct advantages to MgC-GEP, there are also two limitations: MgC-GEP does not determine the absolute expression level of transcripts but the relative abundance of selected transcripts, and the sensitivity of MgC-GEP depends on number of clones sequenced, thus detection of rare transcripts would sequence more clones which will increase the cost. In conclusion, MgC-GEP adopts covnentional RT-PCR, restric- tion enzyme digestion, concatemer ligation, bacterial transforma- tion and DNA sequencing to assess mRNA profiles without using high-throughput expensive methodologies such as microarray hybridization or deep sequencing. No specific equipment is required in this method. This strategy could be of great benefit for labs with limited funds or limited access to microarray or next-generation sequencing facilities. Thus, MgC-GEP should be a potentially powerful tool for multigene expression profiling in different tissues, during development, or during specific pathologies in both basic and pharmaceutical research. PLoS ONE | www.plosone.org 4 January 2011 | Volume 6 | Issue 1 | e15711