Plant Promoters and Terminators for High-Precision Bioengineering.

High-precision bioengineering and synthetic biology require fine-tuning gene expression at both transcriptional and posttranscriptional levels. Gene transcription is tightly regulated by promoters and terminators. Promoters determine the timing, tissues and cells, and levels of the expression of genes. Terminators mediate transcription termination of genes and affect mRNA levels posttranscriptionally, e.g., the 3'-end processing, stability, translation efficiency, and nuclear to cytoplasmic export of mRNAs. The promoter and terminator combination affects gene expression. In the present article, we review the function and features of plant core promoters, proximal and distal promoters, and terminators, and their effects on and benchmarking strategies for regulating gene expression.

Stepwise Optimization of Real-Time RT-PCR Analysis.

Quantitative real-time reverse transcription PCR (qRT-PCR) analysis has been used routinely to quantify gene expression levels. Primer design and the optimization of qRT-PCR parameters are critical for the accuracy and reproducibility of qRT-PCR analysis. Computational tool-assisted primer design often overlooks the presence of homologous sequences of the gene of interest and the sequence similarities between homologous genes in a plant genome. This sometimes results in skipping the optimization of qRT-PCR parameters due to the false confidence in the quality of the designed primers. Here we present a stepwise optimization protocol for single nucleotide polymorphisms (SNPs)-based sequence-specific primer design and sequential optimization of primer sequences, annealing temperatures, primer concentrations, and cDNA concentration range for each reference and target gene. The goal of this optimization protocol is to achieve a standard cDNA concentration curve with an R2 ≥ 0.9999 and efficiency (E) = 100 ± 5% for the best primer pair of each gene, which serves as the prerequisite for using the 2-ΔΔCT method for data analysis.

Coordinated transcriptional regulation of the carotenoid biosynthesis contributes to fruit lycopene content in high-lycopene tomato genotypes.

Lycopene content in tomato fruit is largely under genetic control and varies greatly among genotypes. Continued improvement of lycopene content in elite varieties with conventional breeding has become challenging, in part because little is known about the underlying molecular mechanisms in high-lycopene tomatoes (HLYs). We collected 42 HLYs with different genetic backgrounds worldwide. High-performance liquid chromatography (HPLC) analysis revealed lycopene contents differed among the positive control wild tomato Solanum pimpinellifolium, HLYs, the normal lycopene cultivar "Moneymaker", and the non-lycopene cultivar NC 1Y at the pink and red ripe stages. Real-time RT-PCR analysis of expression of the 25 carotenoid biosynthesis pathway genes of each genotype showed a significantly higher expression in nine upstream genes (GGPPS1, GGPPS2, GGPPS3, TPT1, SSU II, PSY2, ZDS, CrtISO and CrtISO-L1 but not the well-studied PSY1, PDS and Z-ISO) at the breaker and/or red ripe stages in HLYs compared to Moneymaker, indicating a higher metabolic flux flow into carotenoid biosynthesis pathway in HLYs. Further conversion of lycopene to carotenes may be prevented via the two downstream genes (ß-LCY2 and ε-LCY), which had low-abundance transcripts at either or both stages. Additionally, the significantly higher expression of four downstream genes (BCH1, ZEP, VDE, and CYP97C11) at either or both ripeness stages leads to significantly lower fruit lycopene content in HLYs than in the wild tomato. This is the first systematic investigation of the role of the complete pathway genes in regulating fruit lycopene biosynthesis across many HLYs, and enables tomato breeding and gene editing for increased fruit lycopene content.

An optimized protocol for stepwise optimization of real-time RT-PCR analysis.

Computational tool-assisted primer design for real-time reverse transcription (RT) PCR (qPCR) analysis largely ignores the sequence similarities between sequences of homologous genes in a plant genome. It can lead to false confidence in the quality of the designed primers, which sometimes results in skipping the optimization steps for qPCR. However, the optimization of qPCR parameters plays an essential role in the efficiency, specificity, and sensitivity of each gene's primers. Here, we proposed an optimized approach to sequentially optimizing primer sequences, annealing temperatures, primer concentrations, and cDNA concentration range for each reference (and target) gene. Our approach started with a sequence-specific primer design that should be based on the single-nucleotide polymorphisms (SNPs) present in all the homologous sequences for each of the reference (and target) genes under study. By combining the efficiency calibrated and standard curve methods with the 2-ΔΔCt method, the standard cDNA concentration curve with a logarithmic scale was obtained for each primer pair for each gene. As a result, an R2 ≥ 0.9999 and the efficiency (E) = 100 ± 5% should be achieved for the best primer pair of each gene, which serve as the prerequisite for using the 2-ΔΔCt method for data analysis. We applied our newly developed approach to identify the best reference genes in different tissues and at various inflorescence developmental stages of Tripidium ravennae, an ornamental and biomass grass, and validated their utility under varying abiotic stress conditions. We also applied this approach to test the expression stability of six reference genes in soybean under biotic stress treatment with Xanthomonas axonopodis pv. glycines (Xag). Thus, these case studies demonstrated the effectiveness of our optimized protocol for qPCR analysis.