A mechanistic model of PCR for accurate quantification of quantitative PCR data

repDilPCR: a tool for automated analysis of qPCR assays by the dilution-replicate method

BACKGROUND

The dilution-replicate experimental design for qPCR assays is especially efficient. It is based on multiple linear regression of multiple 3-point standard curves that are derived from the experimental samples themselves and thus obviates the need for a separate standard curve produced by serial dilution of a standard. The method minimizes the total number of reactions and guarantees that Cq values are within the linear dynamic range of the dilution-replicate standard curves. However, the lack of specialized software has so far precluded the widespread use of the dilution-replicate approach.

RESULTS

Here we present repDilPCR, the first tool that utilizes the dilution-replicate method and extends it by adding the possibility to use multiple reference genes. repDilPCR offers extensive statistical and graphical functions that can also be used with preprocessed data (relative expression values) obtained by usual assay designs and evaluation methods. repDilPCR has been designed with the philosophy to automate and speed up data analysis (typically less than a minute from Cq values to publication-ready plots), and features automatic selection and performance of appropriate statistical tests, at least in the case of one-factor experimental designs. Nevertheless, the program also allows users to export intermediate data and perform more sophisticated analyses with external statistical software, e.g. if two-way ANOVA is necessary.

CONCLUSIONS

repDilPCR is a user-friendly tool that can contribute to more efficient planning of qPCR experiments and their robust analysis. A public web server is freely accessible at https://repdilpcr.eu without registration. The program can also be used as an R script or as a locally installed Shiny app, which can be downloaded from https://github.com/deyanyosifov/repDilPCR where also the source code is available.

Arogenate dehydratase isoforms strategically deregulate phenylalanine biosynthesis in Akebia trifoliata

Arogenate dehydratase (ADT) is key for phenylalanine (Phe) biosynthesis in plants. To examine ADT components and function in Akebia trifoliata, a representative of Ranunculaceae, we first identified eight ADTs (AktADT1-8, encoding sequences varying from 1032 to 1962 bp) in the A. trifoliata reference genome and five proteins (AktADT1, AktADT4, AktADT7, AktADT8 and AktADT8s) with moonlighting prephenate dehydratase (PDT) activity and Km values varying from 0.43 to 2.17 mM. Structurally, two basic residue combinations (Val314/Ala317 and Ala314/Val317) in the PAC domain are essential for the moonlighting PDT activity of ADTs. Functionally, AktADT4 and AktADT8 successfully restored the wild-type phenotype of pha2, a knockout mutant of Saccharomyces cerevisiae. In addition, AktADTs are ubiquitously expressed, but their expression levels are tissue specific, and the half maximal inhibitory concentration (IC50) of Phe for AktADTs ranged from 49.81 to 331.17 μM. Both AktADT4 and AktADT8 and AktADT8s localized to chloroplast stromules and the cytosol, respectively, while the remaining AktADTs localized to the chloroplast stroma. These findings suggest that various strategies exist for regulating Phe biosynthesis in A. trifoliata. This provides a reasonable explanation for the high Phe content and insights for further genetic improvement of the edible fruits of A. trifoliata.

Properties and Functional Analysis of Two Chorismate Mutases from Maritime Pine

Through the shikimate pathway, a massive metabolic flux connects the central carbon metabolism with the synthesis of chorismate, the common precursor of the aromatic amino acids phenylalanine, tyrosine, and tryptophan, as well as other compounds, including salicylate or folate. The alternative metabolic channeling of chorismate involves a key branch-point, finely regulated by aromatic amino acid levels. Chorismate mutase catalyzes the conversion of chorismate to prephenate, a precursor of phenylalanine and tyrosine and thus a vast repertoire of fundamental derived compounds, such as flavonoids or lignin. The regulation of this enzyme has been addressed in several plant species, but no study has included conifers or other gymnosperms, despite the importance of the phenolic metabolism for these plants in processes such as lignification and wood formation. Here, we show that maritime pine (Pinus pinaster Aiton) has two genes that encode for chorismate mutase, PpCM1 and PpCM2. Our investigations reveal that these genes encode plastidial isoenzymes displaying activities enhanced by tryptophan and repressed by phenylalanine and tyrosine. Using phylogenetic studies, we have provided new insights into the possible evolutionary origin of the cytosolic chorismate mutases in angiosperms involved in the synthesis of phenylalanine outside the plastid. Studies based on different platforms of gene expression and co-expression analysis have allowed us to propose that PpCM2 plays a central role in the phenylalanine synthesis pathway associated with lignification.

Introducing the f0% method: a reliable and accurate approach for qPCR analysis

BACKGROUND

qPCR is a widely used technique in scientific research as a basic tool in gene expression analysis. Classically, the quantitative endpoint of qPCR is the threshold cycle (CT) that ignores differences in amplification efficiency among many other drawbacks. While other methods have been developed to analyze qPCR results, none has statistically proven to perform better than the CT method. Therefore, we aimed to develop a new qPCR analysis method that overcomes the limitations of the CT method. Our f0% [eff naught percent] method depends on a modified flexible sigmoid function to fit the amplification curve with a linear part to subtract the background noise. Then, the initial fluorescence is estimated and reported as a percentage of the predicted maximum fluorescence (f0%).

RESULTS

The performance of the new f0% method was compared against the CT method along with another two outstanding methods-LinRegPCR and Cy0. The comparison regarded absolute and relative quantifications and used 20 dilution curves obtained from 7 different datasets that utilize different DNA-binding dyes. In the case of absolute quantification, f0% reduced CV%, variance, and absolute relative error by 1.66, 2.78, and 1.8 folds relative to CT; and by 1.65, 2.61, and 1.71 folds relative to LinRegPCR, respectively. While, regarding relative quantification, f0% reduced CV% by 1.76, 1.55, and 1.25 folds and variance by 3.13, 2.31, and 1.57 folds regarding CT, LinRegPCR, and Cy0, respectively. Finally, f0% reduced the absolute relative error caused by LinRegPCR by 1.83 folds.

CONCLUSIONS

We recommend using the f0% method to analyze and report qPCR results based on its reported advantages. Finally, to simplify the usage of the f0% method, it was implemented in a macro-enabled Excel file with a user manual located on https://github.com/Mahmoud0Gamal/F0-perc/releases .

Reducing Bias and Quantifying Uncertainty in Fluorescence Produced by PCR

We present a new approach for relating nucleic-acid content to fluorescence in a real-time Polymerase Chain Reaction (PCR) assay. By coupling a two-type branching process for PCR with a fluorescence analog of Beer's Law, the approach reduces bias and quantifies uncertainty in fluorescence. As the two-type branching process distinguishes between complementary strands of DNA, it allows for a stoichiometric description of reactions between fluorescent probes and DNA and can capture the initial conditions encountered in assays targeting RNA. Analysis of the expected copy-number identifies additional dynamics that occur at short times (or, equivalently, low cycle numbers), while investigation of the variance reveals the contributions from liquid volume transfer, imperfect amplification, and strand-specific amplification (i.e., if one strand is synthesized more efficiently than its complement). Linking the branching process to fluorescence by the Beer's Law analog allows for an a priori description of background fluorescence. It also enables uncertainty quantification (UQ) in fluorescence which, in turn, leads to analytical relationships between amplification efficiency (probability) and limit of detection. This work sets the stage for UQ-PCR, where both the input copy-number and its uncertainty are quantified from fluorescence kinetics.

Error-suppression mechanism of PCR by blocker strands

The polymerase chain reaction (PCR) is a central technique in biotechnology. Its ability to amplify a specific target region of a DNA sequence has led to prominent applications, including virus tests, DNA sequencing, genotyping, and genome cloning. These applications rely on the specificity of the primer hybridization and therefore require effective suppression of hybridization errors. A simple and effective method to achieve that is to add blocker strands, also called clamps, to the PCR mixture. These strands bind to the unwanted target sequence, thereby blocking the primer mishybridization. Because of its simplicity, this method is applicable to a broad nucleic-acid-based biotechnology. However, the precise mechanism by which blocker strands suppress PCR errors remains to be understood, limiting the applicability of this technique. Here, we combine experiments and theoretical modeling to reveal this mechanism. We find that the blocker strands both energetically destabilize the mishybridized complex and sculpt a kinetic barrier to suppress mishybridization. This combination of energetic and kinetic biasing extends the viable range of annealing temperatures, which reduces design constraint of the primer sequence and extends the applicability of PCR.

Robust and Precise Quantitative Real-Time Polymerase Chain Reaction with an Amplification Efficiency-Aware Reaction Kinetics Model

Quantitative real-time PCR (qPCR) is a method extensively used in nucleic acid testing for plants and animals. During the coronavirus disease 2019 (COVID-19) pandemic, high-precision qPCR analysis was urgently needed since quantitative results obtained from conventional qPCR methods were not accurate and precise, causing misdiagnoses and high rates of false-negative. To achieve more accurate results, we propose a new qPCR data analysis method with an amplification efficiency-aware reaction kinetics model (AERKM). Our reaction kinetics model (RKM) mathematically describes the tendency of the amplification efficiency during the whole qPCR process inferred by biochemical reaction dynamics. Amplification efficiency (AE) was introduced to rectify the fitted data so as to match the real reaction process for individual tests, thus reducing errors. The 5-point 10-fold gradient qPCR tests of 63 genes have been verified. The results of a 0.9% slope bias and an 8.2% ratio bias using AERKM exceed 4.1 and 39.4%, respectively, of the best performance of existing models, which demonstrates higher precision, less fluctuation, and better robustness among different nucleic acids. AERKM also provides a better understanding of the real qPCR process and gives insights into the detection, treatment, and prevention of severe diseases.

Realizing the value in "non-standard" parts of the qPCR standard curve by integrating fundamentals of quantitative microbiology

The real-time polymerase chain reaction (PCR), commonly known as quantitative PCR (qPCR), is increasingly common in environmental microbiology applications. During the COVID-19 pandemic, qPCR combined with reverse transcription (RT-qPCR) has been used to detect and quantify SARS-CoV-2 in clinical diagnoses and wastewater monitoring of local trends. Estimation of concentrations using qPCR often features a log-linear standard curve model calibrating quantification cycle (Cq) values obtained from underlying fluorescence measurements to standard concentrations. This process works well at high concentrations within a linear dynamic range but has diminishing reliability at low concentrations because it cannot explain "non-standard" data such as Cq values reflecting increasing variability at low concentrations or non-detects that do not yield Cq values at all. Here, fundamental probabilistic modeling concepts from classical quantitative microbiology were integrated into standard curve modeling approaches by reflecting well-understood mechanisms for random error in microbial data. This work showed that data diverging from the log-linear regression model at low concentrations as well as non-detects can be seamlessly integrated into enhanced standard curve analysis. The newly developed model provides improved representation of standard curve data at low concentrations while converging asymptotically upon conventional log-linear regression at high concentrations and adding no fitting parameters. Such modeling facilitates exploration of the effects of various random error mechanisms in experiments generating standard curve data, enables quantification of uncertainty in standard curve parameters, and is an important step toward quantifying uncertainty in qPCR-based concentration estimates. Improving understanding of the random error in qPCR data and standard curve modeling is especially important when low concentrations are of particular interest and inappropriate analysis can unduly affect interpretation, conclusions regarding lab performance, reported concentration estimates, and associated decision-making.

Endothelial Poldip2 regulates sepsis-induced lung injury via Rho pathway activation

AIMS

Sepsis-induced lung injury is associated with significant morbidity and mortality. Previously, we showed that heterozygous deletion of polymerase δ-interacting protein 2 (Poldip2) was protective against sepsis-induced lung injury. Since endothelial barrier disruption is thought to be the main mechanism of sepsis-induced lung injury, we sought to determine if the observed protection was specifically due to the effect of reduced endothelial Poldip2.

METHODS AND RESULTS

Endothelial-specific Poldip2 knock-out mice (EC-/-) and their wild-type littermates (EC+/+) were injected with saline or lipopolysaccharide (18 mg/kg) to model sepsis-induced lung injury. At 18 h post-injection mice, were euthanized and bronchoalveolar lavage (BAL) fluid and lung tissue were collected to assess leucocyte infiltration. Poldip2 EC-/- mice showed reduced lung leucocyte infiltration in BAL (0.21 ± 0.9×106 vs. 1.29 ± 1.8×106 cells/mL) and lung tissue (12.7 ± 1.8 vs. 23 ± 3.7% neutrophils of total number of cells) compared to Poldip2 EC+/+ mice. qPCR analysis of the lung tissue revealed a significantly dampened induction of inflammatory gene expression (TNFα 2.23 ± 0.39 vs. 4.15 ± 0.5-fold, IκBα 4.32 ± 1.53 vs. 8.97 ± 1.59-fold), neutrophil chemoattractant gene expression (CXCL1 68.8 ± 29.6 vs. 147 ± 25.7-fold, CXCL2 65 ± 25.6 vs. 215 ± 27.3-fold) and a marker of endothelial activation (VCAM1 1.25 ± 0.25 vs. 3.8 ± 0.38-fold) in Poldip2 EC-/- compared to Poldip2 EC+/+ lungs. An in vitro model using human pulmonary microvascular endothelial cells was used to assess the effect of Poldip2 knock-down on endothelial activation and permeability. TNFα-induced endothelial permeability and VE-cadherin disruption were significantly reduced with siRNA-mediated knock-down of Poldip2 (5 ± 0.5 vs. 17.5 ± 3-fold for permeability, 1.5 ± 0.4 vs. 10.9 ± 1.3-fold for proportion of disrupted VE-cadherin). Poldip2 knock-down altered expression of Rho-GTPase-related genes, which correlated with reduced RhoA activation by TNFα (0.94 ± 0.05 vs. 1.29 ± 0.01 of relative RhoA activity) accompanied by redistribution of active-RhoA staining to the centre of the cell.

CONCLUSION

Poldip2 is a potent regulator of endothelial dysfunction during sepsis-induced lung injury, and its endothelium-specific inhibition may provide clinical benefit.

Transcriptome Analysis and Intraspecific Variation in Spanish Fir (Abies pinsapo Boiss.)

Spanish fir (Abies pinsapo Boiss.) is an endemic, endangered tree that has been scarcely investigated at the molecular level. In this work, the transcriptome of Spanish fir was assembled, providing a large catalog of expressed genes (22,769), within which a high proportion were full-length transcripts (12,545). This resource is valuable for functional genomics studies and genome annotation in this relict conifer species. Two intraspecific variations of A. pinsapo can be found within its largest population at the Sierra de las Nieves National Park: one with standard green needles and another with bluish-green needles. To elucidate the causes of both phenotypes, we studied different physiological and molecular markers and transcriptome profiles in the needles. "Green" trees showed higher electron transport efficiency and enhanced levels of chlorophyll, protein, and total nitrogen in the needles. In contrast, needles from "bluish" trees exhibited higher contents of carotenoids and cellulose. These results agreed with the differential transcriptomic profiles, suggesting an imbalance in the nitrogen status of "bluish" trees. Additionally, gene expression analyses suggested that these differences could be associated with different epigenomic profiles. Taken together, the reported data provide new transcriptome resources and a better understanding of the natural variation in this tree species, which can help improve guidelines for its conservation and the implementation of adaptive management strategies under climatic change.

Myeloid Poldip2 Contributes to the Development of Pulmonary Inflammation by Regulating Neutrophil Adhesion in a Murine Model of Acute Respiratory Distress Syndrome

Background Lung injury, a severe adverse outcome of lipopolysaccharide-induced acute respiratory distress syndrome, is attributed to excessive neutrophil recruitment and effector response. Poldip2 (polymerase δ-interacting protein 2) plays a critical role in regulating endothelial permeability and leukocyte recruitment in acute inflammation. Thus, we hypothesized that myeloid Poldip2 is involved in neutrophil recruitment to inflamed lungs. Methods and Results After characterizing myeloid-specific Poldip2 knockout mice, we showed that at 18 hours post-lipopolysaccharide injection, bronchoalveolar lavage from myeloid Poldip2-deficient mice contained fewer inflammatory cells (8 [4-16] versus 29 [12-57]×10⁴/mL in wild-type mice) and a smaller percentage of neutrophils (30% [28%-34%] versus 38% [33%-41%] in wild-type mice), while the main chemoattractants for neutrophils remained unaffected. In vitro, Poldip2-deficient neutrophils responded as well as wild-type neutrophils to inflammatory stimuli with respect to neutrophil extracellular trap formation, reactive oxygen species production, and induction of cytokines. However, neutrophil adherence to a tumor necrosis factor-α stimulated endothelial monolayer was inhibited by Poldip2 depletion (225 [115-272] wild-type [myePoldip2^+/+] versus 133 [62-178] myeloid-specific Poldip2 knockout [myePoldip2^-/-] neutrophils) as was transmigration (1.7 [1.3-2.1] versus 1.1 [1.0-1.4] relative to baseline transmigration). To determine the underlying mechanism, we examined the surface expression of β2-integrin, its binding to soluble intercellular adhesion molecule 1, and Pyk2 phosphorylation. Surface expression of β2-integrins was not affected by Poldip2 deletion, whereas β2-integrins and Pyk2 were less activated in Poldip2-deficient neutrophils. Conclusions These results suggest that myeloid Poldip2 is involved in β2-integrin activation during the inflammatory response, which in turn mediates neutrophil-to-endothelium adhesion in lipopolysaccharide-induced acute respiratory distress syndrome.

Characterization of Poldip2 knockout mice: Avoiding incorrect gene targeting

POLDIP2 is a multifunctional protein whose roles are only partially understood. Our laboratory previously reported physiological studies performed using a mouse gene trap model, which suffered from three limitations: perinatal lethality in homozygotes, constitutive Poldip2 inactivation and inadvertent downregulation of the adjacent Tmem199 gene. To overcome these limitations, we developed a new conditional floxed Poldip2 model. The first part of the present study shows that our initial floxed mice were affected by an unexpected mutation, which was not readily detected by Southern blotting and traditional PCR. It consisted of a 305 kb duplication around Poldip2 with retention of the wild type allele and could be traced back to the original targeted ES cell clone. We offer simple suggestions to rapidly detect similar accidents, which may affect genome editing using both traditional and CRISPR-based methods. In the second part of the present study, correctly targeted floxed Poldip2 mice were generated and used to produce a new constitutive knockout line by crossing with a Cre deleter. In contrast to the gene trap model, many homozygous knockout mice were viable, in spite of having no POLDIP2 expression. To further characterize the effects of Poldip2 ablation in the vasculature, RNA-seq and RT-qPCR experiments were performed in constitutive knockout arteries. Results show that POLDIP2 inactivation affects multiple cellular processes and provide new opportunities for future in-depth study of its functions.

Evaluation validation of a qPCR curve analysis method and conventional approaches

BACKGROUND

Reverse Transcription quantitative polymerase chain reaction (RT-qPCR) is a sensitive and reliable method for mRNA quantification and rapid analysis of gene expression from a large number of starting templates. It is based on the statistical significance of the beginning of exponential phase in real-time PCR kinetics, reflecting quantitative cycle of the initial target quantity and the efficiency of the PCR reaction (the fold increase of product per cycle).

RESULTS

We used the large clinical biomarker dataset and 94-replicates-4-dilutions set which was published previously as research tools, then proposed a new qPCR curve analysis method--CqMAN, to determine the position of quantitative cycle as well as the efficiency of the PCR reaction and applied in the calculations. To verify algorithm performance, 20 genes from biomarker and partial data with concentration gradients from 94-replicates-4-dilutions set of MYCN gene were used to compare our method with various publicly available methods and established a suitable evaluation index system.

CONCLUSIONS

The results show that CqMAN method is comparable to other methods and can be a feasible method which applied to our self-developed qPCR data processing and analysis software, providing a simple tool for qPCR analysis.

High resolution estimates of relative gene abundance with quantitative ratiometric regression PCR (qRR-PCR)

Quantification of the relative abundance of genetic traits has broad applications for biomarker discovery, diagnostics, and assessing gene expression in biological research. Relative quantification of genes is traditionally done with the 2-ΔΔCT method using quantitative real-time polymerase chain reaction (qPCR) data, which is often limited in resolution beyond orders of magnitude difference. The latest techniques for quantification of nucleic acids employ digital PCR or microarrays which involve lengthy sample preparation and complex instrumentation. In this work, we describe a quantitative ratiometric regression PCR (qRR-PCR) method for computing relative abundance of genetic traits in a sample with high resolution from a single duplexed real-time quantitative PCR assay. Instead of comparing the individual cycle threshold (Ct) values as is done for the 2-ΔΔCT method, our qRR-PCR algorithm leverages the innate relationship of co-amplified PCR targets to measure their relative quantities using characteristic curves derived from the normalized ratios of qPCR fluorescence curves. We demonstrate the utility of this technique for discriminating the fractional abundance of mixed alleles with resolution below 5%.

Estimating Real-Time qPCR Amplification Efficiency from Single-Reaction Data

Methods for estimating the qPCR amplification efficiency E from data for single reactions are tested on six multireplicate datasets, with emphasis on their performance as a function of the range of cycles n₁–n₂ included in the analysis. The two-parameter exponential growth (EG) model that has been relied upon almost exclusively does not allow for the decline of E(n) with increasing cycle number n through the growth region and accordingly gives low-biased estimates. Further, the standard procedure of “baselining”—separately estimating and subtracting a baseline before analysis—leads to reduced precision. The three-parameter logistic model (LRE) does allow for such decline and includes a parameter E₀ that represents E through the baseline region. Several four-parameter extensions of this model that accommodate some asymmetry in the growth profiles but still retain the significance of E₀ are tested against the LRE and EG models. The recursion method of Carr and Moore also describes a declining E(n) but tacitly assumes E₀ = 2 in the baseline region. Two modifications that permit varying E₀ are tested, as well as a recursion method that directly fits E(n) to a sigmoidal function. All but the last of these can give E₀ estimates that agree fairly well with calibration-based estimates but perform best when the calculations are extended to only about one cycle below the first-derivative maximum (FDM). The LRE model performs as well as any of the four-parameter forms and is easier to use. Its proper implementation requires fitting to it plus a suitable baseline function, which typically requires four–six adjustable parameters in a nonlinear least-squares fit.

Poldip2 controls leukocyte infiltration into the ischemic brain by regulating focal adhesion kinase-mediated VCAM-1 induction

Stroke is a multiphasic process involving a direct ischemic brain injury which is then exacerbated by the influx of immune cells into the brain tissue. Activation of brain endothelial cells leads to the expression of adhesion molecules such vascular cell adhesion molecule 1 (VCAM-1) on endothelial cells, further increasing leukocyte recruitment. Polymerase δ-interacting protein 2 (Poldip2) promotes brain vascular inflammation and leukocyte recruitment via unknown mechanisms. This study aimed to define the role of Poldip2 in mediating vascular inflammation and leukocyte recruitment following cerebral ischemia. Cerebral ischemia was induced in Poldip2+/+ and Poldip2+/- mice and brains were isolated and processed for flow cytometry or RT-PCR. Cultured rat brain microvascular endothelial cells were used to investigate the effect of Poldip2 depletion on focal adhesion kinase (FAK)-mediated VCAM-1 induction. Poldip2 depletion in vivo attenuated the infiltration of myeloid cells, inflammatory monocytes/macrophages and decreased the induction of adhesion molecules. Focusing on VCAM-1, we demonstrated mechanistically that FAK activation was a critical intermediary in Poldip2-mediated VCAM-1 induction. In conclusion, Poldip2 is an important mediator of endothelial dysfunction and leukocyte recruitment. Thus, Poldip2 could be a therapeutic target to improve morbidity following ischemic stroke.

Effect of Quantitative Polymerase Chain Reaction Data Analysis Using Sample Amplification Efficiency on Microbial Source Tracking Assay Performance and Source Attribution

The widely used microbial source tracking (MST) technique, quantitative polymerase chain reaction (qPCR), quantifies host-specific gene abundance in polluted water to identify and prioritize contamination sources. This study characterized the effects of a qPCR data analysis using the sample PCR efficiencies (the LinRegPCR model) on gene abundance and compared them with the standard curve-based method (the mixed model). Five qPCR assays were evaluated: the universal GenBac3, human-specific HF183/BFDrev and CPQ_056, swine-specific Pig-2-Bac, and cattle-specific Bac3qPCR assays. The LinRegPCR model increased the low-copy amplification, especially in the HF183/BFDrev assay, thus lowering the specificity to 0.34. Up to 1.41 log₁₀ copies/g and 0.41 log₁₀ copies/100 mL differences were observed for composite fecal and sewage samples (n = 147) by the LinRegPCR approach, corresponding to an 18.2% increase and 6.4% decrease, respectively. Freshwater samples (n = 48) demonstrated a maximum of 1.95 log₁₀ copies/100 mL difference between the two models. Identical attributing sources by both models were shown in 54.55% of environmental samples; meanwhile, the LinRegPCR approach improved the inability to identify sources by the mixed model in 29.55% of the samples. This study emphasizes the need for a standardized data analysis protocol for qPCR MST assays for interlaboratory consistency and comparability.

Transcriptional analysis of arogenate dehydratase genes identifies a link between phenylalanine biosynthesis and lignin biosynthesis

Biogenesis of the secondary cell wall in trees involves the massive biosynthesis of the phenylalanine-derived polymer lignin. Arogenate dehydratase (ADT) catalyzes the last, and rate-limiting, step of the main pathway for phenylalanine biosynthesis. In this study, we found that transcript levels for several members of the large ADT gene family, including ADT-A and ADT-D, were enhanced in compression wood of maritime pine, a xylem tissue enriched in lignin. Transcriptomic analysis of maritime pine silenced for PpMYB8 revealed that this gene plays a critical role in coordinating the deposition of lignin with the biosynthesis of phenylalanine. Specifically, it was found that ADT-A and ADT-D were strongly down-regulated in PpMYB8-silenced plants and that they were transcriptionally regulated through direct interaction of this transcription factor with regulatory elements present in their promoters. Another transcription factor, PpHY5, exhibited an expression profile opposite to that of PpMYB8 and also interacted with specific regulatory elements of ADT-A and ADT-D genes, suggesting that it is involved in transcriptional regulation of phenylalanine biosynthesis. Taken together, our results reveal that PpMYB8 and PpHY5 are involved in the control of phenylalanine formation and its metabolic channeling for lignin biosynthesis and deposition during wood formation in maritime pine.

Inorganic Nitrogen Form Determines Nutrient Allocation and Metabolic Responses in Maritime Pine Seedlings

Nitrate and ammonium are the main forms of inorganic nitrogen available to plants. The present study aimed to investigate the metabolic changes caused by ammonium and nitrate nutrition in maritime pine (Pinus pinaster Ait.). Seedlings were grown with five solutions containing different proportions of nitrate and ammonium. Their nitrogen status was characterized through analyses of their biomass, different biochemical and molecular markers as well as a metabolite profile using ¹H-NMR. Ammonium-fed seedlings exhibited higher biomass than nitrate-fed-seedlings. Nitrate mainly accumulated in the stem and ammonium in the roots. Needles of ammonium-fed seedlings had higher nitrogen and amino acid contents but lower levels of enzyme activities related to nitrogen metabolism. Higher amounts of soluble sugars and L-arginine were found in the roots of ammonium-fed seedlings. In contrast, L-asparagine accumulated in the roots of nitrate-fed seedlings. The differences in the allocation of nitrate and ammonium may function as metabolic buffers to prevent interference with the metabolism of photosynthetic organs. The metabolite profiles observed in the roots suggest problems with carbon and nitrogen assimilation in nitrate-supplied seedlings. Taken together, this new knowledge contributes not only to a better understanding of nitrogen metabolism but also to improving aspects of applied mineral nutrition for conifers.

qPCR data analysis: Better results through iconoclasm

The standard approach for quantitative estimation of genetic materials with qPCR is calibration with known concentrations for the target substance, in which estimates of the quantification cycle (C_q ) are fitted to a straight-line function of log(N ₀), where N ₀ is the initial number of target molecules. The location of C_q for the unknown on this line then yields its N ₀. The most widely used definition for C_q is an absolute threshold that falls in the early growth cycles. This usage is flawed as commonly implemented: threshold set very close to the baseline level, which is estimated separately, from designated "baseline cycles." The absolute threshold is especially poor for dealing with the scale variability often observed for growth profiles. Scale-independent markers, like the first derivative maximum (FDM) and a relative threshold (C_r ) avoid this problem. We describe improved methods for estimating these and other C_q markers and their standard errors, from a nonlinear algorithm that fits growth profiles to a 4-parameter log-logistic function plus a baseline function. Further, by examining six multidilution, multireplicate qPCR data sets, we find that nonlinear expressions are often preferred statistically for the dependence of C_q on log(N ₀). This means that the amplification efficiency E depends on N ₀, in violation of another tenet of qPCR analysis. Neglect of calibration nonlinearity leads to biased estimates of the unknown. By logic, E estimates from calibration fitting pertain to the earliest baseline cycles, not the early growth cycles used to estimate E from growth profiles for single reactions. This raises concern about the use of the latter in lengthy extrapolations to estimate N ₀. Finally, we observe that replicate ensemble standard deviations greatly exceed predictions, implying that much better results can be achieved from qPCR through better experimental procedures, which likely include reducing pipette volume uncertainty.

Pairwise efficiency: a new mathematical approach to qPCR data analysis increases the precision of the calibration curve assay

Background

The real-time quantitative polymerase chain reaction (qPCR) is routinely used for quantification of nucleic acids and is considered the gold standard in the field of relative nucleic acid measurements. The efficiency of the qPCR reaction is one of the most important parameters in data analysis in qPCR experiments. The Minimum Information for publication of Quantitative real-time PCR Experiments (MIQE) guidelines recommends the calibration curve as the method of choice for estimation of qPCR efficiency. The precision of this method has been reported to be between SD = 0.007 (three replicates) and SD = 0.022 (no replicates).

Results

In this article, we present a novel approach to the analysis of qPCR data which has been obtained by running a dilution series. Unlike previously developed methods, our method, Pairwise Efficiency, involves a new formula that describes pairwise relationships between data points on separate amplification curves and thus enables extensive statistics. The comparison of Pairwise Efficiency with the calibration curve by Monte Carlo simulation shows the two-folds improvement in the precision of estimations of efficiency and gene expression ratios on the same dataset.

Conclusions

The Pairwise Efficiency nearly doubles the precision in qPCR efficiency determinations compared to standard calibration curve method. This paper demonstrates that applications of combinatorial treatment of data provide the improvement of the determination.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2911-5) contains supplementary material, which is available to authorized users.

The cofilin phosphatase slingshot homolog 1 restrains angiotensin II-induced vascular hypertrophy and fibrosis in vivo

The dual specificity phosphatase slingshot homolog 1 (SSH1) contributes to actin remodeling by dephosphorylating and activating the actin-severing protein cofilin. The reorganization of the actin cytoskeleton has been implicated in chronic hypertension and the subsequent mechano-adaptive rearrangement of vessel wall components. Therefore, using a novel Ssh1^-/- mouse model, we investigated the potential role of SSH1 in angiotensin II (Ang II)-induced hypertension, and vascular remodeling. We found that loss of SSH1 did not produce overt phenotypic changes and that baseline blood pressures as well as heart rates were comparable between Ssh1^+/+ and Ssh1^-/- mice. Although 14 days of Ang II treatment equally increased systolic blood pressure in both genotypes, histological assessment of aortic samples indicated that medial thickening was exacerbated by the loss of SSH1. Consequently, reverse-transcription quantitative PCR analysis of the transcripts from Ang II-infused animals confirmed increased aortic expression levels of fibronectin, and osteopontin in Ssh1^-/- when compared to wild-type mice. Mechanistically, our data suggest that fibrosis in SSH1-deficient mice occurs by a process that involves aberrant responses to Ang II-induced TGFβ1. Taken together, our work indicates that Ang II-dependent fibrotic gene expression and vascular remodeling, but not the Ang II-induced pressor response, are modulated by SSH1-mediated signaling pathways and SSH1 activity is protective against Ang II-induced remodeling in the vasculature.

Poldip2 deficiency protects against lung edema and vascular inflammation in a model of acute respiratory distress syndrome

Acute respiratory distress syndrome (ARDS) in a deadly disease that can be brought on by endotoxins such as lipopolysaccharide (LPS). ARDS is characterized by vascular permeability, a severe inflammatory response, lung leukocyte infiltration, and resultant lung edema. Polymerase δ-interacting protein 2 (Poldip2) is a novel regulator of blood-brain barrier permeability; however, its role in regulating lung permeability and vascular inflammation is unknown. Here, the role of Poldip2 in regulating vascular permeability and inflammation in a mouse model of ARDS was assessed. Heterozygous deletion of Poldip2 was found to reduce LPS-induced mortality within 20 h, lung inflammatory signaling, and leukocyte infiltration. Moreover, reduced Poldip2-suppressed LP-induced vascular cell adhesion molecule (VCAM)-1 induction, leukocyte recruitment, and mitochondrial reactive oxygen species (ROS) production in vitro These data indicate that Poldip2 is an important regulator of the debilitating consequences of ARDS, potentially through the regulation of mitochondrial ROS-induced inflammatory signaling. Consequently, inhibition of Poldip2 may be a viable option for therapeutic discovery moving forward.

Algorithms for automated detection of hook effect-bearing amplification curves

Amplification curves from quantitative Real-Time PCR experiments typically exhibit a sigmoidal shape. They can roughly be divided into a ground or baseline phase, an exponential amplification phase, a linear phase and finally a plateau phase, where in the latter, the PCR product concentration no longer increases. Nevertheless, in some cases the plateau phase displays a negative trend, e.g. in hydrolysis probe assays. This cycle-to-cycle fluorescence decrease is commonly referred to in the literature as the hook effect. Other detection chemistries also exhibit this negative trend, however the underlying molecular mechanisms are different.

In this study we present two approaches to automatically detect hook effect-like curvatures based on linear (hookreg) and nonlinear regression (hookregNL). As the hook effect is typical for qPCR data, both algorithms can be employed for the automated identification of regular structured qPCR curves. Therefore, our algorithms streamline quality control, but can also be used for assay optimization or machine learning.

A minimally parametrized branching process explaining plateau phase of qPCR amplification

Quantitative polymerase chain reaction (qPCR) is a commonly used molecular biology technique for measuring the concentration of a target nucleic acid sequence in a sample. The whole qPCR amplification process usually consists of an exponential, a linear and a plateau phase. In qPCR experiments, amplification curves of samples with different template concentrations often, even though not always, have the same plateau height. The biological theory for this phenomenon is that the plateau height is determined by reaction kinetics. Does it mean that the target concentration has no effect on the final plateau height? We proposed a branching process based on Michaelis-Menten kinetics. Our model can describe all phases of qPCR amplification despite its simplicity (it depends on only one parameter). We theoretically showed, through almost sure convergence, that amplification curves will eventually plateau at finite values in any experiment, under any condition. We conclude that the plateau height is largely determined by reaction kinetics but could also be affected by the template concentration. This is in accordance with the current biological theory.

Tackling critical parameters in metazoan meta-barcoding experiments: a preliminary study based on coxI DNA barcode

Nowadays DNA meta-barcoding is a powerful instrument capable of quickly discovering the biodiversity of an environmental sample by integrating the DNA barcoding approach with High Throughput Sequencing technologies. It mainly consists of the parallel reading of informative genomic fragment/s able to discriminate living entities. Although this approach has been widely studied, it still needs optimization in some necessary steps requested in its advanced accomplishment. A fundamental element concerns the standardization of bioinformatic analyses pipelines. The aim of the present study was to underline a number of critical parameters of laboratory material preparation and taxonomic assignment pipelines in DNA meta-barcoding experiments using the cytochrome oxidase subunit-I (coxI) barcode region, known as a suitable molecular marker for animal species identification. We compared nine taxonomic assignment pipelines, including a custom in-house method, based on Hidden Markov Models. Moreover, we evaluated the potential influence of universal primers amplification bias in qPCR, as well as the correlation between GC content with taxonomic assignment results. The pipelines were tested on a community of known terrestrial invertebrates collected by pitfall traps from a chestnut forest in Italy. Although the present analysis was not exhaustive and needs additional investigation, our results suggest some potential improvements in laboratory material preparation and the introduction of additional parameters in taxonomic assignment pipelines. These include the correct setup of OTU clustering threshold, the calibration of GC content affecting sequencing quality and taxonomic classification, as well as the evaluation of PCR primers amplification bias on the final biodiversity pattern. Thus, careful attention and further validation/optimization of the above-mentioned variables would be required in a DNA meta-barcoding experimental routine.

Polymerase delta-interacting protein 2 deficiency protects against blood-brain barrier permeability in the ischemic brain

BACKGROUND

Polymerase δ-interacting protein 2 (Poldip2) is a multifunctional protein that regulates vascular extracellular matrix composition and matrix metalloproteinase (MMP) activity. The blood-brain barrier (BBB) is a dynamic system assembled by endothelial cells, basal lamina, and perivascular astrocytes, raising the possibility that Poldip2 may be involved in maintaining its structure. We investigated the role of Poldip2 in the late BBB permeability induced by cerebral ischemia.

METHODS

Transient middle cerebral artery occlusion (tMCAO) was induced in Poldip2+/+ and Poldip2+/- mice. The volume of the ischemic lesion was measured in triphenyltetrazolium chloride-stained sections. BBB breakdown was evaluated by Evans blue dye extravasation. Poldip2 protein expression was evaluated by western blotting. RT-PCR, zymography, and ELISAs were used to measure mRNA levels, activity, and protein levels of cytokines and MMPs. Cultured astrocytes were transfected with Poldip2 siRNA, and mRNA levels of cytokines were evaluated as well as IκBα protein degradation.

RESULTS

Cerebral ischemia induced the expression of Poldip2. Compared to Poldip2+/+ mice, Poldip2+/- animals exhibited decreased Evans blue dye extravasation and improved survival 24 h following stroke. Poldip2 expression was upregulated in astrocytes exposed to oxygen and glucose deprivation (OGD) and siRNA-mediated downregulation of Poldip2 abrogated OGD-induced IL-6 and TNF-α expression. In addition, siRNA against Poldip2 inhibited TNF-α-induced IκBα degradation. TNF-α, IL-6, MCP-1, VEGF, and MMP expression induced by cerebral ischemia was abrogated in Poldip2+/- mice. The protective effect of Poldip2 depletion on the increased permeability of the BBB was partially reversed by systemic administration of TNF-α.

CONCLUSIONS

Poldip2 is upregulated following ischemic stroke and mediates the breakdown of the BBB by increasing cerebral cytokine production and MMP activation. Therefore, Poldip2 appears to be a promising novel target for the development of therapeutic strategies to prevent the development of cerebral edema in the ischemic brain.

The gene expression landscape of pine seedling tissues

Conifers dominate vast regions of the Northern hemisphere. They are the main source of raw materials for timber industry as well as a wide range of biomaterials. Despite their inherent difficulties as experimental models for classical plant biology research, the technological advances in genomics research are enabling fundamental studies on these plants. The use of laser capture microdissection followed by transcriptomic analysis is a powerful tool for unravelling the molecular and functional organization of conifer tissues and specialized cells. In the present work, 14 different tissues from 1-month-old maritime pine (Pinus pinaster) seedlings have been isolated and their transcriptomes analysed. The results increased the sequence information and number of full-length transcripts from a previous reference transcriptome and added 39 841 new transcripts. In total, 2376 transcripts were ubiquitously expressed in all of the examined tissues. These transcripts could be considered the core 'housekeeping genes' in pine. The genes have been clustered in function to their expression profiles. This analysis reduced the number of profiles to 38, most of these defined by their expression in a unique tissue that is much higher than in the other tissues. The expression and localization data are accessible at ConGenIE.org (http://v22.popgenie.org/microdisection/). This study presents an overview of the gene expression distribution in different pine tissues, specifically highlighting the relationships between tissue gene expression and function. This transcriptome atlas is a valuable resource for functional genomics research in conifers.

A Novel RNA Phosphorylation State Enables 5' End-Dependent Degradation in Escherichia coli

RNA modifications that once escaped detection are now thought to be pivotal for governing RNA lifetimes in both prokaryotes and eukaryotes. For example, converting the 5'-terminal triphosphate of bacterial transcripts to a monophosphate triggers 5' end-dependent degradation by RNase E. However, the existence of diphosphorylated RNA in bacteria has never been reported, and no biological role for such a modification has ever been proposed. By using a novel assay, we show here for representative Escherichia coli mRNAs that ~35%-50% of each transcript is diphosphorylated. The remainder is primarily monophosphorylated, with surprisingly little triphosphorylated RNA evident. Furthermore, diphosphorylated RNA is the preferred substrate of the RNA pyrophosphohydrolase RppH, whose biological function was previously assumed to be pyrophosphate removal from triphosphorylated transcripts. We conclude that triphosphate-to-monophosphate conversion to induce 5' end-dependent RNA degradation is a two-step process in E. coli involving γ-phosphate removal by an unidentified enzyme to enable subsequent β-phosphate removal by RppH.

System-specific periodicity in quantitative real-time polymerase chain reaction data questions threshold-based quantitation

Real-time quantitative polymerase chain reaction (qPCR) data are found to display periodic patterns in the fluorescence intensity as a function of sample number for fixed cycle number. This behavior is seen for technical replicate datasets recorded on several different commercial instruments; it occurs in the baseline region and typically increases with increasing cycle number in the growth and plateau regions. Autocorrelation analysis reveals periodicities of 12 for 96-well systems and 24 for a 384-well system, indicating a correlation with block architecture. Passive dye experiments show that the effect may be from optical detector bias. Importantly, the signal periodicity manifests as periodicity in quantification cycle (C_q) values when these are estimated by the widely applied fixed threshold approach, but not when scale-insensitive markers like first- and second-derivative maxima are used. Accordingly, any scale variability in the growth curves will lead to bias in constant-threshold-based C_qs, making it mandatory that workers should either use scale-insensitive C_qs or normalize their growth curves to constant amplitude before applying the constant threshold method.

Root-shoot interactions explain the reduction of leaf mineral content in Arabidopsis plants grown under elevated [CO2 ] conditions

Although shoot N depletion in plants exposed to elevated [CO2 ] has already been reported on several occasions, some uncertainty remains about the mechanisms involved. This study illustrates (1) the importance of characterizing root-shoot interactions and (2) the physiological, biochemical and gene expression mechanisms adopted by nitrate-fed Arabidopsis thaliana plants grown under elevated [CO2 ]. Elevated [CO2 ] increases biomass and photosynthetic rates; nevertheless, the decline in total soluble protein, Rubisco and leaf N concentrations revealed a general decrease in leaf N availability. A transcriptomic approach (conducted at the root and shoot level) revealed that exposure to 800 ppm [CO2 ] induced the expression of genes involved in the transport of nitrate and mineral elements. Leaf N and mineral status revealed that N assimilation into proteins was constrained under elevated [CO2 ]. Moreover, this study also highlights how elevated [CO2 ] induced the reorganization of nitrate assimilation between tissues; root nitrogen assimilation was favored over leaf assimilation to offset the decline in nitrogen metabolism in the leaves of plants exposed to elevated [CO2 ].

A Versatile Panel of Reference Gene Assays for the Measurement of Chicken mRNA by Quantitative PCR

Quantitative real-time PCR assays are widely used for the quantification of mRNA within avian experimental samples. Multiple stably-expressed reference genes, selected for the lowest variation in representative samples, can be used to control random technical variation. Reference gene assays must be reliable, have high amplification specificity and efficiency, and not produce signals from contaminating DNA. Whilst recent research papers identify specific genes that are stable in particular tissues and experimental treatments, here we describe a panel of ten avian gene primer and probe sets that can be used to identify suitable reference genes in many experimental contexts. The panel was tested with TaqMan and SYBR Green systems in two experimental scenarios: a tissue collection and virus infection of cultured fibroblasts. GeNorm and NormFinder algorithms were able to select appropriate reference gene sets in each case. We show the effects of using the selected genes on the detection of statistically significant differences in expression. The results are compared with those obtained using 28s ribosomal RNA, the present most widely accepted reference gene in chicken work, identifying circumstances where its use might provide misleading results. Methods for eliminating DNA contamination of RNA reduced, but did not completely remove, detectable DNA. We therefore attached special importance to testing each qPCR assay for absence of signal using DNA template. The assays and analyses developed here provide a useful resource for selecting reference genes for investigations of avian biology.

Identification of a small protein domain present in all plant lineages that confers high prephenate dehydratase activity

l-Phenylalanine serves as a building block for the biosynthesis of proteins, but also as a precursor for a wide range of plant-derived compounds essential for plants and animals. Plants can synthesize Phe within the plastids using arogenate as a precursor; however, an alternative pathway using phenylpyruvate as an intermediate, described for most microorganisms, has recently been proposed. The functionality of this pathway requires the existence of enzymes with prephenate dehydratase (PDT) activity (EC 4.2.1.51) in plants. Using phylogenetic studies, functional complementation assays in yeast and biochemical analysis, we have identified the enzymes displaying PDT activity in Pinus pinaster. Through sequence alignment comparisons and site-directed mutagenesis we have identified a 22-amino acid region conferring PDT activity (PAC domain) and a single Ala314 residue critical to trigger this activity. Our results demonstrate that all plant clades include PAC domain-containing ADTs, suggesting that the PDT activity, and thus the ability to synthesize Phe using phenylpyruvate as an intermediate, has been preserved throughout the evolution of plants. Moreover, this pathway together with the arogenate pathway gives plants a broad and versatile capacity to synthesize Phe and its derived compounds. PAC domain-containing enzymes are also present in green and red algae, and glaucophytes, the three emerging clades following the primary endosymbiont event resulting in the acquisition of plastids in eukaryotes. The evolutionary prokaryotic origin of this domain is discussed.

Quantification of Cooperativity in Heterodimer-DNA Binding Improves the Accuracy of Binding Specificity Models

Many transcription factors (TFs) have the ability to cooperate on DNA elements as heterodimers. Despite the significance of TF heterodimerization for gene regulation, a quantitative understanding of cooperativity between various TF dimer partners and its impact on heterodimer DNA binding specificity models is still lacking. Here, we used a novel integrative approach, combining microfluidics-steered measurements of dimer-DNA assembly with mechanistic modeling of the implicated protein-protein-DNA interactions to quantitatively interrogate the cooperative DNA binding behavior of the adipogenic peroxisome proliferator-activated receptor γ (PPARγ):retinoid X receptor α (RXRα) heterodimer. Using the high throughput MITOMI (mechanically induced trapping of molecular interactions) platform, we derived equilibrium DNA binding data for PPARγ, RXRα, as well as the PPARγ:RXRα heterodimer to more than 300 target DNA sites and variants thereof. We then quantified cooperativity underlying heterodimer-DNA binding and derived an integrative heterodimer DNA binding constant. Using this cooperativity-inclusive constant, we were able to build a heterodimer-DNA binding specificity model that has superior predictive power than the one based on a regular one-site equilibrium. Our data further revealed that individual nucleotide substitutions within the target site affect the extent of cooperativity in PPARγ:RXRα-DNA binding. Our study therefore emphasizes the importance of assessing cooperativity when generating DNA binding specificity models for heterodimers.

Redox-Sensitive Regulation of Myocardin-Related Transcription Factor (MRTF-A) Phosphorylation via Palladin in Vascular Smooth Muscle Cell Differentiation Marker Gene Expression

Vascular smooth muscle cells (VSMCs) undergo a phenotypic switch from a differentiated to synthetic phenotype in cardiovascular diseases such as atherosclerosis and restenosis. Our previous studies indicate that transforming growth factor-β (TGF-β) helps to maintain the differentiated phenotype by regulating expression of pro-differentiation genes such as smooth muscle α-actin (SMA) and Calponin (CNN) through reactive oxygen species (ROS) derived from NADPH oxidase 4 (Nox4) in VSMCs. In this study, we investigated the relationship between Nox4 and myocardin-related transcription factor-A (MRTF-A), a transcription factor known to be important in expression of smooth muscle marker genes. Previous work has shown that MRTF-A interacts with the actin-binding protein, palladin, although how this interaction affects MRTF-A function is unclear, as is the role of phosphorylation in MRTF-A activity. We found that Rho kinase (ROCK)-mediated phosphorylation of MRTF-A is a key event in the regulation of SMA and CNN in VSMCs and that this phosphorylation depends upon Nox4-mediated palladin expression. Knockdown of Nox4 using siRNA decreases TGF-β -induced palladin expression and MRTF-A phosphorylation, suggesting redox-sensitive regulation of this signaling pathway. Knockdown of palladin also decreases MRTF-A phosphorylation. These data suggest that Nox4-dependent palladin expression and ROCK regulate phosphorylation of MRTF-A, a critical factor in the regulation of SRF responsive gene expression.

Mathematics analysis of polymerase chain reaction kinetic curves

The paper reviews different approaches to the mathematical analysis of polymerase chain reaction (PCR) kinetic curves. The basic principles of PCR mathematical analysis are presented. Approximation of PCR kinetic curves and PCR efficiency curves by various functions is described. Several PCR models based on chemical kinetics equations are suggested. Decision criteria for an optimal function to describe PCR efficiency are proposed.

Poplar trees for phytoremediation of high levels of nitrate and applications in bioenergy

The utilization of high amounts of nitrate fertilizers for crop yield leads to nitrate pollution of ground and surface waters. In this study, we report the assimilation and utilization of nitrate luxuriant levels, 20 times more than the highest N fertilizer application in Europe, by transgenic poplars overexpressing a cytosolic glutamine synthetase (GS1). In comparison with the wild-type controls, transgenic plants grown under high N levels exhibited increased biomass (171.6%) and accumulated higher levels of proteins, chlorophylls and total sugars such as glucose, fructose and sucrose. These plants also exhibited greater nitrogen-use efficiency particularly in young leaves, suggesting that they are able to translocate most of the resources to the above-ground part of the plant to produce biomass. The transgenic poplar transcriptome was greatly affected in response to N availability with 1237 genes differentially regulated in high N, while only 632 genes were differentially expressed in untransformed plants. Many of these genes are essential in the adaptation and response against N excess and include those involved in photosynthesis, cell wall formation and phenylpropanoid biosynthesis. Cellulose production in the transgenic plants was fivefold higher than in control plants, indicating that transgenic poplars represent a potential feedstock for applications in bioenergy. In conclusion, our results show that GS transgenic poplars can be used not only for improving growth and biomass production but also as an important resource for potential phytoremediation of nitrate pollution.

The overexpression of the pine transcription factor PpDof5 in Arabidopsis leads to increased lignin content and affects carbon and nitrogen metabolism

PpDof 5 is a regulator of the expression of glutamine synthetase (GS; EC 6.3.1.2) genes in photosynthetic and non-photosynthetic tissues of maritime pine. We have used Arabidopsis thaliana as a model system to study PpDof 5 function in planta, generating transgenic lines overexpressing the pine transcription factor. The overexpression of PpDof 5 resulted in a substantial increase of lignin content with a simultaneous regulation of carbon and nitrogen key genes. In addition, partitioning in carbon and nitrogen compounds was spread via various secondary metabolic pathways. These results suggest pleiotropic effects of PpDof 5 expression on various metabolic pathways of carbon and nitrogen metabolism. Plants overexpressing PpDof 5 exhibited upregulation of genes encoding enzymes for sucrose and starch biosynthesis, with a parallel increase in the content of soluble sugars. When the plants were grown under nitrate as the sole nitrogen source, they exhibited a significant regulation of the expression of genes involved mainly in signaling, but similar growth rates to wild-type plants. However, plants grown under ammonium exhibited major induction of the expression of photosynthetic genes and differential expression of ammonium and nitrate transporters. All these data suggest that in addition to controlling ammonium assimilation, PpDof 5 could be also involved in the regulation of other pathways in carbon and nitrogen metabolism in pine trees.

Transcriptome-wide analysis supports environmental adaptations of two Pinus pinaster populations from contrasting habitats

BACKGROUND

Maritime pine (Pinus pinaster Aiton) grows in a range of different climates in the southwestern Mediterranean region and the existence of a variety of latitudinal ecotypes or provenances is well established. In this study, we have conducted a deep analysis of the transcriptome in needles from two P. pinaster provenances, Leiria (Portugal) and Tamrabta (Morocco), which were grown in northern Spain under the same conditions.

RESULTS

An oligonucleotide microarray (PINARRAY3) and RNA-Seq were used for whole-transcriptome analyses, and we found that 90.95% of the data were concordant between the two platforms. Furthermore, the two methods identified very similar percentages of differentially expressed genes with values of 5.5% for PINARRAY3 and 5.7% for RNA-Seq. In total, 6,023 transcripts were shared and 88 differentially expressed genes overlapped in the two platforms. Among the differentially expressed genes, all transport related genes except aquaporins were expressed at higher levels in Tamrabta than in Leiria. In contrast, genes involved in secondary metabolism were expressed at higher levels in Tamrabta, and photosynthesis-related genes were expressed more highly in Leiria. The genes involved in light sensing in plants were well represented in the differentially expressed groups of genes. In addition, increased levels of hormones such as abscisic acid, gibberellins, jasmonic and salicylic acid were observed in Leiria.

CONCLUSIONS

Both transcriptome platforms have proven to be useful resources, showing complementary and reliable results. The results presented here highlight the different abilities of the two maritime pine populations to sense environmental conditions and reveal one type of regulation that can be ascribed to different genetic and epigenetic backgrounds.

Root and shoot performance of Arabidopsis thaliana exposed to elevated CO2: A physiologic, metabolic and transcriptomic response

The responsiveness of C3 plants to raised atmospheric [CO2] levels has been frequently described as constrained by photosynthetic downregulation. The main goal of the current study was to characterize the shoot-root relationship and its implications in plant responsiveness under elevated [CO2] conditions. For this purpose, Arabidopsis thaliana plants were exposed to elevated [CO2] (800ppm versus 400ppm [CO2]) and fertilized with a mixed (NH4NO3) nitrogen source. Plant growth, physiology, metabolite and transcriptomic characterizations were carried out at the root and shoot levels. Plant growth under elevated [CO2] conditions was doubled due to increased photosynthetic rates and gas exchange measurements revealed that these plants maintain higher photosynthetic rates over extended periods of time. This positive response of photosynthetic rates to elevated [CO2] was caused by the maintenance of leaf protein and Rubisco concentrations at control levels alongside enhanced energy efficiency. The increased levels of leaf carbohydrates, organic acids and amino acids supported the augmented respiration rates of plants under elevated [CO2]. A transcriptomic analysis allowed the identification of photoassimilate allocation and remobilization as fundamental process used by the plants to maintain the outstanding photosynthetic performance. Moreover, based on the relationship between plant carbon status and hormone functioning, the transcriptomic analyses provided an explanation of why phenology accelerates under elevated [CO2] conditions.

Understanding developmental and adaptive cues in pine through metabolite profiling and co-expression network analysis

Conifers include long-lived evergreen trees of great economic and ecological importance, including pines and spruces. During their long lives conifers must respond to seasonal environmental changes, adapt to unpredictable environmental stresses, and co-ordinate their adaptive adjustments with internal developmental programmes. To gain insights into these responses, we examined metabolite and transcriptomic profiles of needles from naturally growing 25-year-old maritime pine (Pinus pinaster L. Aiton) trees over a year. The effect of environmental parameters such as temperature and rain on needle development were studied. Our results show that seasonal changes in the metabolite profiles were mainly affected by the needles' age and acclimation for winter, but changes in transcript profiles were mainly dependent on climatic factors. The relative abundance of most transcripts correlated well with temperature, particularly for genes involved in photosynthesis or winter acclimation. Gene network analysis revealed relationships between 14 co-expressed gene modules and development and adaptation to environmental stimuli. Novel Myb transcription factors were identified as candidate regulators during needle development. Our systems-based analysis provides integrated data of the seasonal regulation of maritime pine growth, opening new perspectives for understanding the complex regulatory mechanisms underlying conifers' adaptive responses. Taken together, our results suggest that the environment regulates the transcriptome for fine tuning of the metabolome during development.

Isothermal strand displacement amplification (iSDA): a rapid and sensitive method of nucleic acid amplification for point-of-care diagnosis

A new rapid and sensitive method of isothermal DNA amplification and a simple kinetic model of this reaction network.

Transcriptome analysis in maritime pine using laser capture microdissection and 454 pyrosequencing

Maritime pine (Pinus pinaster Aiton) is one of the most advanced conifer models for genomics research. Conifer genomes are extremely large and major advances have recently been made in the characterization of transcriptomes. The combination of laser capture microdissection (LCM) and next-generation sequencing is a powerful tool with which to resolve the entire transcriptome of specific cell types and tissues. In the current work, we have developed a protocol for transcriptomic analyses of conifer tissue types using LCM and 454 pyrosequencing. Tissue sections were isolated using non-fixed flash-frozen samples processed by LCM. Complementary DNA synthesis and amplification from tiny amounts of total RNA from LCM samples was performed using an adapted protocol for C: onifer R: NA A: mplification (CRA+). The cDNA amplification yield and cDNA quality provided by CRA+ were adequate for 454 pyrosequencing. Furthermore, read length and quality results of the 454 runs were near the optimal parameters considered by Roche for transcriptome sequencing. Using the CRA+ protocol, non-specific amplifications were prevented, problems derived from poly(A:T) tails in the 454 sequencing technology were reduced, and read length and read number considerably enhanced. This technical approach will facilitate global gene expression analysis in individual tissues of conifers and may also be applied to other plant species.

A survey of tools for the analysis of quantitative PCR (qPCR) data

Real-time quantitative polymerase-chain-reaction (qPCR) is a standard technique in most laboratories used for various applications in basic research. Analysis of qPCR data is a crucial part of the entire experiment, which has led to the development of a plethora of methods. The released tools either cover specific parts of the workflow or provide complete analysis solutions. Here, we surveyed 27 open-access software packages and tools for the analysis of qPCR data. The survey includes 8 Microsoft Windows, 5 web-based, 9 R-based and 5 tools from other platforms. Reviewed packages and tools support the analysis of different qPCR applications, such as RNA quantification, DNA methylation, genotyping, identification of copy number variations, and digital PCR. We report an overview of the functionality, features and specific requirements of the individual software tools, such as data exchange formats, availability of a graphical user interface, included procedures for graphical data presentation, and offered statistical methods. In addition, we provide an overview about quantification strategies, and report various applications of qPCR. Our comprehensive survey showed that most tools use their own file format and only a fraction of the currently existing tools support the standardized data exchange format RDML. To allow a more streamlined and comparable analysis of qPCR data, more vendors and tools need to adapt the standardized format to encourage the exchange of data between instrument software, analysis tools, and researchers.

Brachyury cooperates with Wnt/β-catenin signalling to elicit primitive-streak-like behaviour in differentiating mouse embryonic stem cells

Background

The formation of the primitive streak is the first visible sign of gastrulation, the process by which the three germ layers are formed from a single epithelium during early development. Embryonic stem cells (ESCs) provide a good system for understanding the molecular and cellular events associated with these processes. Previous work, both in embryos and in culture, has shown how converging signals from both nodal/TGFβR and Wnt/β-catenin signalling pathways specify cells to adopt a primitive-streak-like fate and direct them to undertake an epithelial-to-mesenchymal transition (EMT). However, many of these approaches have relied on genetic analyses without taking into account the temporal progression of events within single cells. In addition, it is still unclear to what extent events in the embryo are able to be reproduced in culture.

Results

Here, we combine flow cytometry and a quantitative live single-cell imaging approach to demonstrate how the controlled differentiation of mouse ESCs towards a primitive streak fate in culture results in cells displaying many of the characteristics observed during early mouse development including transient brachyury expression, EMT and increased motility. We also find that the EMT initiates the process, and this is both fuelled and terminated by the action of brachyury, whose expression is dependent on the EMT and β-catenin activity.

Conclusions

As a consequence of our analysis, we propose that a major output of brachyury expression is in controlling the velocity of the cells that are transiting out of the primitive streak.

Electronic supplementary material

The online version of this article (doi:10.1186/s12915-014-0063-7) contains supplementary material, which is available to authorized users.

Modeling bi-modality improves characterization of cell cycle on gene expression in single cells

Advances in high-throughput, single cell gene expression are allowing interrogation of cell heterogeneity. However, there is concern that the cell cycle phase of a cell might bias characterizations of gene expression at the single-cell level. We assess the effect of cell cycle phase on gene expression in single cells by measuring 333 genes in 930 cells across three phases and three cell lines. We determine each cell's phase non-invasively without chemical arrest and use it as a covariate in tests of differential expression. We observe bi-modal gene expression, a previously-described phenomenon, wherein the expression of otherwise abundant genes is either strongly positive, or undetectable within individual cells. This bi-modality is likely both biologically and technically driven. Irrespective of its source, we show that it should be modeled to draw accurate inferences from single cell expression experiments. To this end, we propose a semi-continuous modeling framework based on the generalized linear model, and use it to characterize genes with consistent cell cycle effects across three cell lines. Our new computational framework improves the detection of previously characterized cell-cycle genes compared to approaches that do not account for the bi-modality of single-cell data. We use our semi-continuous modelling framework to estimate single cell gene co-expression networks. These networks suggest that in addition to having phase-dependent shifts in expression (when averaged over many cells), some, but not all, canonical cell cycle genes tend to be co-expressed in groups in single cells. We estimate the amount of single cell expression variability attributable to the cell cycle. We find that the cell cycle explains only 5%–17% of expression variability, suggesting that the cell cycle will not tend to be a large nuisance factor in analysis of the single cell transcriptome.

Recent technological advances have enabled the measurement of gene expression in individual cells, revealing that there is substantial variability in expression, even within a homogeneous cell population. In this paper, we develop new analytical methods that account for the intrinsic, stochastic nature of single cell expression in order to characterize the effect of cell cycle on gene expression at the single-cell level. Applying these methods to populations of asynchronously cycling cells, we are able to identify large numbers of genes with cell cycle-associated expression patterns. By measuring and adjusting for cellular-level factors, we are able to derive estimates of co-expressing gene networks that more closely reflect cellular-level processes as opposed to sample-level processes. We find that cell cycle phase only accounts for a modest amount of the overall variability of gene expression within an individual cell. The analytical methods demonstrated in this paper are universally applicable to single cell expression data and represent a promising tool to the scientific community.

Statistical uncertainty and its propagation in the analysis of quantitative polymerase chain reaction data: comparison of methods

Most methods for analyzing real-time quantitative polymerase chain reaction (qPCR) data for single experiments estimate the hypothetical cycle 0 signal y0 by first estimating the quantification cycle (Cq) and amplification efficiency (E) from least-squares fits of fluorescence intensity data for cycles near the onset of the growth phase. The resulting y0 values are statistically equivalent to the corresponding Cq if and only if E is taken to be error free. But uncertainty in E usually dominates the total uncertainty in y0, making the latter much degraded in precision compared with Cq. Bias in E can be an even greater source of error in y0. So-called mechanistic models achieve higher precision in estimating y0 by tacitly assuming E=2 in the baseline region and so are subject to this bias error. When used in calibration, the mechanistic y0 is statistically comparable to Cq from the other methods. When a signal threshold yq is used to define Cq, best estimation precision is obtained by setting yq near the maximum signal in the range of fitted cycles, in conflict with common practice in the y0 estimation algorithms.