Joshua S. Yuan

Statistical analysis of real-time PCR data

BackgroundEven though real-time PCR has been broadly applied in biomedical sciences, data processing procedures for the analysis of quantitative real-time PCR are still lacking; specifically in the realm of appropriate statistical treatment. Confidence interval and statistical significance considerations are not explicit in many of the current data analysis approaches. Based on the standard curve method and other useful data analysis methods, we present and compare four statistical approaches and models for the analysis of real-time PCR data.ResultsIn the first approach, a multiple regression analysis model was developed to derive ΔΔCt from estimation of interaction of gene and treatment effects. In the second approach, an ANCOVA (analysis of covariance) model was proposed, and the ΔΔCt can be derived from analysis of effects of variables. The other two models involve calculation ΔCt followed by a two group t- test and non-parametric analogous Wilcoxon test. SAS programs were developed for all four models and data output for analysis of a sample set are presented. In addition, a data quality control model was developed and implemented using SAS.ConclusionPractical statistical solutions with SAS programs were developed for real-time PCR data and a sample dataset was analyzed with the SAS programs. The analysis using the various models and programs yielded similar results. Data quality control and analysis procedures presented here provide statistical elements for the estimation of the relative expression of genes using real-time PCR.

Plants to power: bioenergy to fuel the future

Bioenergy should play an essential part in reaching targets to replace petroleum-based transportation fuels with a viable alternative, and in reducing long-term carbon dioxide emissions, if environmental and economic sustainability are considered carefully. Here, we review different platforms, crops, and biotechnology-based improvements for sustainable bioenergy. Among the different platforms, there are two obvious advantages to using lignocellulosic biomass for ethanol production: higher net energy gain and lower production costs. However, the use of lignocellulosic ethanol as a viable alternative to petroleum-based transportation fuels largely depends on plant biotechnology breakthroughs. We examine how biotechnology, such as lignin modification, abiotic stress resistance, nutrition usage, in planta expression of cell wall digestion enzymes, biomass production, feedstock establishment, biocontainment of transgenes, metabolic engineering, and basic research, can be used to address the challenges faced by bioenergy crop production.

Redesigning photosynthesis to sustainably meet global food and bioenergy demand

The world’s crop productivity is stagnating whereas population growth, rising affluence, and mandates for biofuels put increasing demands on agriculture. Meanwhile, demand for increasing cropland competes with equally crucial global sustainability and environmental protection needs. Addressing this looming agricultural crisis will be one of our greatest scientific challenges in the coming decades, and success will require substantial improvements at many levels. We assert that increasing the efficiency and productivity of photosynthesis in crop plants will be essential if this grand challenge is to be met. Here, we explore an array of prospective redesigns of plant systems at various scales, all aimed at increasing crop yields through improved photosynthetic efficiency and performance. Prospects range from straightforward alterations, already supported by preliminary evidence of feasibility, to substantial redesigns that are currently only conceptual, but that may be enabled by new developments in synthetic biology. Although some proposed redesigns are certain to face obstacles that will require alternate routes, the efforts should lead to new discoveries and technical advances with important impacts on the global problem of crop productivity and bioenergy production.

Comparative genome analysis of lignin biosynthesis gene families across the plant kingdom.

BackgroundAs a major component of plant cell wall, lignin plays important roles in mechanical support, water transport, and stress responses. As the main cause for the recalcitrance of plant cell wall, lignin modification has been a major task for bioenergy feedstock improvement. The study of the evolution and function of lignin biosynthesis genes thus has two-fold implications. First, the lignin biosynthesis pathway provides an excellent model to study the coordinative evolution of a biochemical pathway in plants. Second, understanding the function and evolution of lignin biosynthesis genes will guide us to develop better strategies for bioenergy feedstock improvement.ResultsWe analyzed lignin biosynthesis genes from fourteen plant species and one symbiotic fungal species. Comprehensive comparative genome analysis was carried out to study the distribution, relatedness, and family expansion of the lignin biosynthesis genes across the plant kingdom. In addition, we also analyzed the comparative synteny map between rice and sorghum to study the evolution of lignin biosynthesis genes within the Poaceae family and the chromosome evolution between the two species. Comprehensive lignin biosynthesis gene expression analysis was performed in rice, poplar and Arabidopsis. The representative data from rice indicates that different fates of gene duplications exist for lignin biosynthesis genes. In addition, we also carried out the biomass composition analysis of nine Arabidopsis mutants with both MBMS analysis and traditional wet chemistry methods. The results were analyzed together with the genomics analysis.ConclusionThe research revealed that, among the species analyzed, the complete lignin biosynthesis pathway first appeared in moss; the pathway is absent in green algae. The expansion of lignin biosynthesis gene families correlates with substrate diversity. In addition, we found that the expansion of the gene families mostly occurred after the divergence of monocots and dicots, with the exception of the C4H gene family. Gene expression analysis revealed different fates of gene duplications, largely confirming plants are tolerant to gene dosage effects. The rapid expansion of lignin biosynthesis genes indicated that the translation of transgenic lignin modification strategies from model species to bioenergy feedstock might only be successful between the closely relevant species within the same family.

Transcriptional responses of Arabidopsis thaliana plants to As (V) stress

BackgroundArsenic is toxic to plants and a common environmental pollutant. There is a strong chemical similarity between arsenate [As (V)] and phosphate (Pi). Whole genome oligonucleotide microarrays were employed to investigate the transcriptional responses of Arabidopsis thaliana plants to As (V) stress.ResultsAntioxidant-related genes (i.e. coding for superoxide dismutases and peroxidases) play prominent roles in response to arsenate. The microarray experiment revealed induction of chloroplast Cu/Zn superoxide dismutase (SOD) (at2g28190), Cu/Zn SOD (at1g08830), as well as an SOD copper chaperone (at1g12520). On the other hand, Fe SODs were strongly repressed in response to As (V) stress. Non-parametric rank product statistics were used to detect differentially expressed genes. Arsenate stress resulted in the repression of numerous genes known to be induced by phosphate starvation. These observations were confirmed with qRT-PCR and SOD activity assays.ConclusionMicroarray data suggest that As (V) induces genes involved in response to oxidative stress and represses transcription of genes induced by phosphate starvation. This study implicates As (V) as a phosphate mimic in the cell by repressing genes normally induced when available phosphate is scarce. Most importantly, these data reveal that arsenate stress affects the expression of several genes with little or unknown biological functions, thereby providing new putative gene targets for future research.

Molecular and genomic basis of volatile‐mediated indirect defense against insects in rice

Rice plants fed on by fall armyworm (Spodoptera frugiperda, FAW) caterpillars emit a blend of volatiles dominated by terpenoids. These volatiles were highly attractive to females of the parasitoid Cotesia marginiventris. Microarray analysis identified 196 rice genes whose expression was significantly upregulated by FAW feeding, 18 of which encode metabolic enzymes potentially involved in volatile biosynthesis. Significant induction of expression of seven of the 11 terpene synthase (TPS) genes identified through the microarray experiments was confirmd using real-time RT-PCR. Enzymes encoded by three TPS genes, Os02g02930, Os08g07100 and Os08g04500, were biochemically characterized. Os02g02930 was found to encode a monoterpene synthase producing the single product S-linalool, which is the most abundant volatile emitted from FAW-damaged rice plants. Both Os08g07100 and Os08g04500 were found to encode sesquiterpene synthases, each producing multiple products. These three enzymes are responsible for production of the majority of the terpenes released from FAW-damaged rice plants. In addition to TPS genes, several key genes in the upstream terpenoid pathways were also found to be upregulated by FAW feeding. This paper provides a comprehensive analysis of FAW-induced volatiles and the corresponding volatile biosynthetic genes potentially involved in indirect defense in rice. Evolution of the genetic basis governing volatile terpenoid biosynthesis for indirect defense is discussed.

Smelling global climate change: mitigation of function for plant volatile organic compounds

Plant volatile organic compounds (VOCs) have important roles in plant adaptation to the environment and serve as infochemicals in multitrophic interactions. Global climate change factors, such as increased atmospheric carbon dioxide, ozone and temperature, could alter how insects perceive such compounds. Here we review recent research on the influence of climate change parameters on the ecological functions of VOCs, with specific focus on terpenoids, the best-characterized VOCs. We summarize how emission patterns and concentrations of VOCs could change in future environments, mainly from the perspectives of plant defense and stress responses. We discuss how higher carbon dioxide concentrations, elevated ozone levels and increased temperatures could affect the biological functions of VOCs, particularly their role in plant defense.

Characterization of the horseweed (Conyza canadensis) transcriptome using GS-FLX 454 pyrosequencing and its application for expression analysis of candidate non-target herbicide resistance genes.

BACKGROUND The de novo transcriptome sequencing of a weedy plant using GS-FLX 454 technologies is reported. Horseweed (Conyza canadensis L.) was the first broadleaf weed to evolve glyphosate resistance in agriculture, and also is the most widely distributed glyphosate-resistant weed in the United States and the world. However, available sequence data for this species are scant. The transcriptomic sequence should be useful for gene discovery, and to help elucidate the non-target-based glyphosate resistance mechanism and the genomic basis of weediness. RESULTS Sequencing experiments yielded 411 962 raw reads, an average read length of 233 bp and a total dataset of 95.8 Mb (NCBI accession number SRA010952). After trimming and quality control, 379 152 high-quality sequences were retained and assembled into contigs. The assembly resulted in 31 783 unique transcripts, including 16 102 contigs and 15 681 singletons. The average coverage depth for each contig and each nucleotide position was 22-fold and 12-fold respectively. A total of 16 306 unique sequences were annotated by searching a custom plant protein database. The utility of the transcriptome data was demonstrated by further exploration of ABC transporters, which were previously hypothesized to play a role in non-target glyphosate resistance. Real-time RT-PCR primers were designed from the transcriptome data, which made it possible to assess expression patterns of 17 ABC transporters from resistant and susceptible horseweed accessions from Tennessee, with and without glyphosate treatment. CONCLUSION These results show that GS-FLX 454 sequencing is a powerful and cost-effective platform for the development of functional genomic tools for a weed species.

Statistical tools for transgene copy number estimation based on real-time PCR

BackgroundAs compared with traditional transgene copy number detection technologies such as Southern blot analysis, real-time PCR provides a fast, inexpensive and high-throughput alternative. However, the real-time PCR based transgene copy number estimation tends to be ambiguous and subjective stemming from the lack of proper statistical analysis and data quality control to render a reliable estimation of copy number with a prediction value. Despite the recent progresses in statistical analysis of real-time PCR, few publications have integrated these advancements in real-time PCR based transgene copy number determination.ResultsThree experimental designs and four data quality control integrated statistical models are presented. For the first method, external calibration curves are established for the transgene based on serially-diluted templates. The Ct number from a control transgenic event and putative transgenic event are compared to derive the transgene copy number or zygosity estimation. Simple linear regression and two group T-test procedures were combined to model the data from this design. For the second experimental design, standard curves were generated for both an internal reference gene and the transgene, and the copy number of transgene was compared with that of internal reference gene. Multiple regression models and ANOVA models can be employed to analyze the data and perform quality control for this approach. In the third experimental design, transgene copy number is compared with reference gene without a standard curve, but rather, is based directly on fluorescence data. Two different multiple regression models were proposed to analyze the data based on two different approaches of amplification efficiency integration. Our results highlight the importance of proper statistical treatment and quality control integration in real-time PCR-based transgene copy number determination.ConclusionThese statistical methods allow the real-time PCR-based transgene copy number estimation to be more reliable and precise with a proper statistical estimation. Proper confidence intervals are necessary for unambiguous prediction of trangene copy number. The four different statistical methods are compared for their advantages and disadvantages. Moreover, the statistical methods can also be applied for other real-time PCR-based quantification assays including transfection efficiency analysis and pathogen quantification.

Molecular approaches to study the insect gut symbiotic microbiota at the 'omics' age

Abstract  Insect gut symbiotic microbiota play essential roles in the growth, development, pathogenesis and environmental adaptation of host insects. The molecular and systems level analysis of insect gut symbiotic microbial community will allow us to discover novel biocatalysts for biomass deconstruction and to develop innovative strategies for pest management. We hereby review the various molecular biology techniques as applied to insect gut symbiont analysis. This review aims to serve as an informative resource for experimental design and research strategy development in the field. We first discuss various strategies for sample preparation and their pros and cons. The traditional molecular techniques like DGGE, RFLP and FISH are covered with respect to how they are applied to study the composition, diversity and dynamics of insect gut symbiotic microbiota. We then focus on the various ‘omics’ techniques. The metagenome analysis together with the recent advancements in next‐generation sequencing will provide enormous sequencing information, allowing in‐depth microbial diversity analysis and modeling of pathways for biological processes such as biomass degradation. The metagenome sequencing will also enable the study of system dynamics and gene expression with metatranscriptome and metaproteome methods. The integration of different ‘omics’ level data will allow us to understand how insect gut works as a system to carry out its functions. The molecular and systems‐level understanding will also guide the reverse design of next‐generation biorefinery.