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1.  RTPrimerDB: the portal for real-time PCR primers and probes 
Nucleic Acids Research  2008;37(Database issue):D942-D945.
RTPrimerDB (http://www.rtprimerdb.org) is a freely accessible database and analysis tool for real-time quantitative PCR assays. RTPrimerDB includes records with user submitted assays that are linked to genome information from reference databases and quality controlled using an in silico assay evaluation system. The primer evaluation tools intended to assess the specificity and to detect features that could negatively affect the amplification efficiency are combined into a pipeline to test custom-designed primer and probe sequences. An improved user feedback system guides users and submitters to enter practical remarks and details about experimental evaluation analyses. The database is linked with reference databases to allow the submission of assays for all genes and organisms officially registered in Entrez Gene and RefSeq. Records in RTPrimerDB are assigned unique and stable identifiers. The content is provided via an interactive web-based search system and is available for download in the recently developed RDML format and as bulk export file. RTPrimerDB is a one-stop portal for high-quality and highly annotated real-time PCR assays.
doi:10.1093/nar/gkn777
PMCID: PMC2686610  PMID: 18948285
2.  Five Years MIQE Guidelines: The Case of the Arabian Countries 
PLoS ONE  2014;9(2):e88266.
The quantitative real time polymerase chain reaction (qPCR) has become a key molecular enabling technology with an immense range of research, clinical, forensic as well as diagnostic applications. Its relatively moderate instrumentation and reagent requirements have led to its adoption by numerous laboratories, including those located in the Arabian world, where qPCR, which targets DNA, and reverse transcription qPCR (RT-qPCR), which targets RNA, are widely used for region-specific biotechnology, agricultural and human genetic studies. However, it has become increasingly apparent that there are significant problems with both the quality of qPCR-based data as well as the transparency of reporting. This realisation led to the publication of the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines in 2009 and their more widespread adoption in the last couple of years. An analysis of the performance of biomedical research in the Arabian world between 2001–2005 suggests that the Arabian world is producing fewer biomedical publications of lower quality than other Middle Eastern countries. Hence we have analysed specifically the quality of RT-qPCR-based peer-reviewed papers published since 2009 from Arabian researchers using a bespoke iOS/Android app developed by one of the authors. Our results show that compliance with 15 essential MIQE criteria was low (median of 40%, range 0–93%) and few details on RNA quality controls (22% compliance), assays design (12%), RT strategies (32%), amplification efficiencies (30%) and the normalisation process (3%). These data indicate that one of the reasons for the poor performance of Arabian world biomedical research may be the low standard of any supporting qPCR experiments and identify which aspects of qPCR experiments require significant improvements.
doi:10.1371/journal.pone.0088266
PMCID: PMC3913779  PMID: 24505456
3.  A MIQE-Compliant Real-Time PCR Assay for Aspergillus Detection 
PLoS ONE  2012;7(7):e40022.
The polymerase chain reaction (PCR) is widely used as a diagnostic tool in clinical laboratories and is particularly effective for detecting and identifying infectious agents for which routine culture and microscopy methods are inadequate. Invasive fungal disease (IFD) is a major cause of morbidity and mortality in immunosuppressed patients, and optimal diagnostic criteria are contentious. Although PCR-based methods have long been used for the diagnosis of invasive aspergillosis (IA), variable performance in clinical practice has limited their value. This shortcoming is a consequence of differing sample selection, collection and preparation protocols coupled with a lack of standardisation of the PCR itself. Furthermore, it has become clear that the performance of PCR-based assays in general is compromised by the inadequacy of experimental controls, insufficient optimisation of assay performance as well as lack of transparency in reporting experimental details. The recently published “Minimum Information for the publication of real-time Quantitative PCR Experiments” (MIQE) guidelines provide a blueprint for good PCR assay design and unambiguous reporting of experimental detail and results. We report the first real-time quantitative PCR (qPCR) assay targeting Aspergillus species that has been designed, optimised and validated in strict compliance with the MIQE guidelines. The hydrolysis probe-based assay, designed to target the 18S rRNA DNA sequence of Aspergillus species, has an efficiency of 100% (range 95–107%), a dynamic range of at least six orders of magnitude and limits of quantification and detection of 6 and 0.6 Aspergillus fumigatus genomes, respectively. It does not amplify Candida, Scedosporium, Fusarium or Rhizopus species and its clinical sensitivity is demonstrated in histological material from proven IA cases, as well as concordant PCR and galactomannan data in matched broncho-alveolar lavage and blood samples. The robustness, specificity and sensitivity of this assay make it an ideal molecular diagnostic tool for clinical use.
doi:10.1371/journal.pone.0040022
PMCID: PMC3393739  PMID: 22808087
4.  Evaluation of qPCR reference genes in two genotypes of Populus for use in photoperiod and low-temperature studies 
BMC Research Notes  2012;5:366.
Background
Quantitative PCR (qPCR) is a widely used technique for gene expression analysis. A common normalization method for accurate qPCR data analysis involves stable reference genes to determine relative gene expression. Despite extensive research in the forest tree species Populus, there is not a resource for reference genes that meet the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) standards for qPCR techniques and analysis. Since Populus is a woody perennial species, studies of seasonal changes in gene expression are important towards advancing knowledge of this important developmental and physiological trait. The objective of this study was to evaluate reference gene expression stability in various tissues and growth conditions in two important Populus genotypes (P. trichocarpa “Nisqually 1” and P. tremula x P. alba 717 1-B4) following MIQE guidelines.
Results
We evaluated gene expression stability in shoot tips, young leaves, mature leaves and bark tissues from P. trichocarpa and P. tremula. x P. alba grown under long-day (LD), short-day (SD) or SD plus low-temperatures conditions. Gene expression data were analyzed for stable reference genes among 18S rRNA, ACT2, CDC2, CYC063, TIP4-like, UBQ7, PT1 and ANT using two software packages, geNormPLUS and BestKeeper. GeNormPLUS ranked TIP4-like and PT1 among the most stable genes in most genotype/tissue combinations while BestKeeper ranked CDC2 and ACT2 among the most stable genes.
Conclusions
This is the first comprehensive evaluation of reference genes in two important Populus genotypes and the only study in Populus that meets MIQE standards. Both analysis programs identified stable reference genes in both genotypes and all tissues grown under different photoperiods. This set of reference genes was found to be suitable for either genotype considered here and may potentially be suitable for other Populus species and genotypes. These results provide a valuable resource for the Populus research community.
doi:10.1186/1756-0500-5-366
PMCID: PMC3479007  PMID: 22824181
RT-qPCR; Reference gene validation; Populus trichocarpa; Populus tremula x Populus alba
5.  Selection of reference genes for qPCR in hairy root cultures of peanut 
BMC Research Notes  2011;4:392.
Background
Hairy root cultures produced via Agrobacterium rhizogenes-mediated transformation have emerged as practical biological models to elucidate the biosynthesis of specialized metabolites. To effectively understand the expression patterns of the genes involved in the metabolic pathways of these compounds, reference genes need to be systematically validated under specific experimental conditions as established by the MIQE (Minimum Information for Publication of Quantitative Real-Time PCR Experiments) guidelines. In the present report we describe the first validation of reference genes for RT-qPCR in hairy root cultures of peanut which produce stilbenoids upon elicitor treatments.
Results
A total of 21 candidate reference genes were evaluated. Nineteen genes were selected based on previous qPCR studies in plants and two were from the T-DNAs transferred from A. rhizogenes. Nucleotide sequences of peanut candidate genes were obtained using their homologous sequences in Arabidopsis. To identify the suitable primers, calibration curves were obtained for each candidate reference gene. After data analysis, 12 candidate genes meeting standard efficiency criteria were selected. The expression stability of these genes was analyzed using geNorm and NormFinder algorithms and a ranking was established based on expression stability of the genes. Candidate reference gene expression was shown to have less variation in methyl jasmonate (MeJA) treated root cultures than those treated with sodium acetate (NaOAc).
Conclusions
This work constitutes the first effort to validate reference genes for RT-qPCR in hairy roots. While these genes were selected under conditions of NaOAc and MeJA treatment, we anticipate these genes to provide good targets for reference genes for hairy roots under a variety of stress conditions. The lead reference genes were a gene encoding for a TATA box binding protein (TBP2) and a gene encoding a ribosomal protein (RPL8C). A commonly used reference gene GAPDH showed low stability of expression suggesting that its use may lead to inaccurate gene expression profiles when used for data normalization in stress-stimulated hairy roots. Likewise the A. rhizogenes transgene rolC showed less expression stability than GAPDH. This study proposes that a minimum of two reference genes should be used for a normalization procedure in gene expression profiling using elicited hairy roots.
doi:10.1186/1756-0500-4-392
PMCID: PMC3199266  PMID: 21985172
6.  BactQuant: An enhanced broad-coverage bacterial quantitative real-time PCR assay 
BMC Microbiology  2012;12:56.
Background
Bacterial load quantification is a critical component of bacterial community analysis, but a culture-independent method capable of detecting and quantifying diverse bacteria is needed. Based on our analysis of a diverse collection of 16 S rRNA gene sequences, we designed a broad-coverage quantitative real-time PCR (qPCR) assay—BactQuant—for quantifying 16 S rRNA gene copy number and estimating bacterial load. We further utilized in silico evaluation to complement laboratory-based qPCR characterization to validate BactQuant.
Methods
The aligned core set of 4,938 16 S rRNA gene sequences in the Greengenes database were analyzed for assay design. Cloned plasmid standards were generated and quantified using a qPCR-based approach. Coverage analysis was performed computationally using >670,000 sequences and further evaluated following the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines.
Results
A bacterial TaqMan® qPCR assay targeting a 466 bp region in V3-V4 was designed. Coverage analysis showed that 91% of the phyla, 96% of the genera, and >80% of the 89,537 species analyzed contained at least one perfect sequence match to the BactQuant assay. Of the 106 bacterial species evaluated, amplification efficiencies ranged from 81 to 120%, with r2-value of >0.99, including species with sequence mismatches. Inter- and intra-run coefficient of variance was <3% and <16% for Ct and copy number, respectively.
Conclusions
The BactQuant assay offers significantly broader coverage than a previously reported universal bacterial quantification assay BactQuant in vitro performance was better than the in silico predictions.
doi:10.1186/1471-2180-12-56
PMCID: PMC3464140  PMID: 22510143
7.  Quantification Bias Caused by Plasmid DNA Conformation in Quantitative Real-Time PCR Assay 
PLoS ONE  2011;6(12):e29101.
Quantitative real-time PCR (qPCR) is the gold standard for the quantification of specific nucleic acid sequences. However, a serious concern has been revealed in a recent report: supercoiled plasmid standards cause significant over-estimation in qPCR quantification. In this study, we investigated the effect of plasmid DNA conformation on the quantification of DNA and the efficiency of qPCR. Our results suggest that plasmid DNA conformation has significant impact on the accuracy of absolute quantification by qPCR. DNA standard curves shifted significantly among plasmid standards with different DNA conformations. Moreover, the choice of DNA measurement method and plasmid DNA conformation may also contribute to the measurement error of DNA standard curves. Due to the multiple effects of plasmid DNA conformation on the accuracy of qPCR, efforts should be made to assure the highest consistency of plasmid standards for qPCR. Thus, we suggest that the conformation, preparation, quantification, purification, handling, and storage of standard plasmid DNA should be described and defined in the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) to assure the reproducibility and accuracy of qPCR absolute quantification.
doi:10.1371/journal.pone.0029101
PMCID: PMC3237602  PMID: 22194997
8.  FungiQuant: A broad-coverage fungal quantitative real-time PCR assay 
BMC Microbiology  2012;12:255.
Background
Fungal load quantification is a critical component of fungal community analyses. Limitation of current approaches for quantifying the fungal component in the human microbiome suggests the need for new broad-coverage techniques.
Methods
We analyzed 2,085 18S rRNA gene sequences from the SILVA database for assay design. We generated and quantified plasmid standards using a qPCR-based approach. We evaluated assay coverage against 4,968 sequences and performed assay validation following the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines.
Results
We designed FungiQuant, a TaqMan® qPCR assay targeting a 351 bp region in the fungal 18S rRNA gene. Our in silico analysis showed that FungiQuant is a perfect sequence match to 90.0% of the 2,617 fungal species analyzed. We showed that FungiQuant’s is 100% sensitive and its amplification efficiencies ranged from 76.3% to 114.5%, with r2-values of >0.99 against the 69 fungal species tested. Additionally, FungiQuant inter- and intra-run coefficients of variance ranged from <10% and <20%, respectively. We further showed that FungiQuant has a limit of quantification 25 copies and a limit of detection at 5 copies. Lastly, by comparing results from human-only background DNA with low-level fungal DNA, we showed that amplification in two or three of a FungiQuant performed in triplicate is statistically significant for true positive fungal detection.
Conclusions
FungiQuant has comprehensive coverage against diverse fungi and is a robust quantification and detection tool for delineating between true fungal detection and non-target human DNA.
doi:10.1186/1471-2180-12-255
PMCID: PMC3565980  PMID: 23136846
9.  FuGEFlow: data model and markup language for flow cytometry 
BMC Bioinformatics  2009;10:184.
Background
Flow cytometry technology is widely used in both health care and research. The rapid expansion of flow cytometry applications has outpaced the development of data storage and analysis tools. Collaborative efforts being taken to eliminate this gap include building common vocabularies and ontologies, designing generic data models, and defining data exchange formats. The Minimum Information about a Flow Cytometry Experiment (MIFlowCyt) standard was recently adopted by the International Society for Advancement of Cytometry. This standard guides researchers on the information that should be included in peer reviewed publications, but it is insufficient for data exchange and integration between computational systems. The Functional Genomics Experiment (FuGE) formalizes common aspects of comprehensive and high throughput experiments across different biological technologies. We have extended FuGE object model to accommodate flow cytometry data and metadata.
Methods
We used the MagicDraw modelling tool to design a UML model (Flow-OM) according to the FuGE extension guidelines and the AndroMDA toolkit to transform the model to a markup language (Flow-ML). We mapped each MIFlowCyt term to either an existing FuGE class or to a new FuGEFlow class. The development environment was validated by comparing the official FuGE XSD to the schema we generated from the FuGE object model using our configuration. After the Flow-OM model was completed, the final version of the Flow-ML was generated and validated against an example MIFlowCyt compliant experiment description.
Results
The extension of FuGE for flow cytometry has resulted in a generic FuGE-compliant data model (FuGEFlow), which accommodates and links together all information required by MIFlowCyt. The FuGEFlow model can be used to build software and databases using FuGE software toolkits to facilitate automated exchange and manipulation of potentially large flow cytometry experimental data sets. Additional project documentation, including reusable design patterns and a guide for setting up a development environment, was contributed back to the FuGE project.
Conclusion
We have shown that an extension of FuGE can be used to transform minimum information requirements in natural language to markup language in XML. Extending FuGE required significant effort, but in our experiences the benefits outweighed the costs. The FuGEFlow is expected to play a central role in describing flow cytometry experiments and ultimately facilitating data exchange including public flow cytometry repositories currently under development.
doi:10.1186/1471-2105-10-184
PMCID: PMC2711079  PMID: 19531228
10.  Cell-free microRNAs: potential biomarkers in need of standardized reporting 
MicroRNAs are abundantly present and surprisingly stable in multiple biological fluids. These findings have been followed by numerous reverse transcription real-time quantitative PCR (RT-qPCR)-based reports revealing the clinical potential of using microRNA levels in body fluids as a biomarker of disease. Despite a rapidly increasing body of literature, the field has failed to adopt a set of standardized criteria for reporting the methodology used in the quantification of cell-free microRNAs. Not only do many studies based on RT-qPCR fail to address the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) criteria but frequently there is also a distinct lack of detail in descriptions of sample source and RNA isolation. As a direct result, it is often impossible to compare the results of different studies, which in turn, hinders progress in the field. To address this point, we propose a simple set of criteria to be used in conjunction with MIQE to reveal the true potential of cell-free microRNAs as biomarkers.
doi:10.3389/fgene.2013.00056
PMCID: PMC3630323  PMID: 23626598
cell-free microRNA; isolation; quantification; reporting; standard
11.  Evidence Based Selection of Commonly Used RT-qPCR Reference Genes for the Analysis of Mouse Skeletal Muscle 
PLoS ONE  2014;9(2):e88653.
The ability to obtain accurate and reproducible data using quantitative real-time Polymerase Chain Reaction (RT-qPCR) is limited by the process of data normalization. The use of ‘housekeeping’ or ‘reference’ genes is the most common technique used to normalize RT-qPCR data. However, commonly used reference genes are often poorly validated and may change as a result of genetic background, environment and experimental intervention. Here we present an analysis of 10 reference genes in mouse skeletal muscle (Actb, Aldoa, Gapdh, Hprt1, Ppia, Rer1, Rn18s, Rpl27, Rpl41 and Rpl7L1), which were identified as stable either by microarray or in the literature. Using the MIQE guidelines we compared wild-type (WT) mice across three genetic backgrounds (R129, C57BL/6j and C57BL/10) as well as analyzing the α-actinin-3 knockout (Actn3 KO) mouse, which is a model of the common null polymorphism (R577X) in human ACTN3. Comparing WT mice across three genetic backgrounds, we found that different genes were more tightly regulated in each strain. We have developed a ranked profile of the top performing reference genes in skeletal muscle across these common mouse strains. Interestingly the commonly used reference genes; Gapdh, Rn18s, Hprt1 and Actb were not the most stable. Analysis of our experimental variant (Actn3 KO) also resulted in an altered ranking of reference gene suitability. Furthermore we demonstrate that a poor reference gene results in increased variability in the normalized expression of a gene of interest, and can result in loss of significance. Our data demonstrate that reference genes need to be validated prior to use. For the most accurate normalization, it is important to test several genes and use the geometric mean of at least three of the most stably expressed genes. In the analysis of mouse skeletal muscle, strain and intervention played an important role in selecting the most stable reference genes.
doi:10.1371/journal.pone.0088653
PMCID: PMC3921188  PMID: 24523926
12.  Nuclear Receptor Expression Defines a Set of Prognostic Biomarkers for Lung Cancer 
PLoS Medicine  2010;7(12):e1000378.
David Mangelsdorf and colleagues show that nuclear receptor expression is strongly associated with clinical outcomes of lung cancer patients, and this expression profile is a potential prognostic signature for lung cancer patient survival time, particularly for individuals with early stage disease.
Background
The identification of prognostic tumor biomarkers that also would have potential as therapeutic targets, particularly in patients with early stage disease, has been a long sought-after goal in the management and treatment of lung cancer. The nuclear receptor (NR) superfamily, which is composed of 48 transcription factors that govern complex physiologic and pathophysiologic processes, could represent a unique subset of these biomarkers. In fact, many members of this family are the targets of already identified selective receptor modulators, providing a direct link between individual tumor NR quantitation and selection of therapy. The goal of this study, which begins this overall strategy, was to investigate the association between mRNA expression of the NR superfamily and the clinical outcome for patients with lung cancer, and to test whether a tumor NR gene signature provided useful information (over available clinical data) for patients with lung cancer.
Methods and Findings
Using quantitative real-time PCR to study NR expression in 30 microdissected non-small-cell lung cancers (NSCLCs) and their pair-matched normal lung epithelium, we found great variability in NR expression among patients' tumor and non-involved lung epithelium, found a strong association between NR expression and clinical outcome, and identified an NR gene signature from both normal and tumor tissues that predicted patient survival time and disease recurrence. The NR signature derived from the initial 30 NSCLC samples was validated in two independent microarray datasets derived from 442 and 117 resected lung adenocarcinomas. The NR gene signature was also validated in 130 squamous cell carcinomas. The prognostic signature in tumors could be distilled to expression of two NRs, short heterodimer partner and progesterone receptor, as single gene predictors of NSCLC patient survival time, including for patients with stage I disease. Of equal interest, the studies of microdissected histologically normal epithelium and matched tumors identified expression in normal (but not tumor) epithelium of NGFIB3 and mineralocorticoid receptor as single gene predictors of good prognosis.
Conclusions
NR expression is strongly associated with clinical outcomes for patients with lung cancer, and this expression profile provides a unique prognostic signature for lung cancer patient survival time, particularly for those with early stage disease. This study highlights the potential use of NRs as a rational set of therapeutically tractable genes as theragnostic biomarkers, and specifically identifies short heterodimer partner and progesterone receptor in tumors, and NGFIB3 and MR in non-neoplastic lung epithelium, for future detailed translational study in lung cancer.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Lung cancer, the most common cause of cancer-related death, kills 1.3 million people annually. Most lung cancers are “non-small-cell lung cancers” (NSCLCs), and most are caused by smoking. Exposure to chemicals in smoke causes changes in the genes of the cells lining the lungs that allow the cells to grow uncontrollably and to move around the body. How NSCLC is treated and responds to treatment depends on its “stage.” Stage I tumors, which are small and confined to the lung, are removed surgically, although chemotherapy is also sometimes given. Stage II tumors have spread to nearby lymph nodes and are treated with surgery and chemotherapy, as are some stage III tumors. However, because cancer cells in stage III tumors can be present throughout the chest, surgery is not always possible. For such cases, and for stage IV NSCLC, where the tumor has spread around the body, patients are treated with chemotherapy alone. About 70% of patients with stage I and II NSCLC but only 2% of patients with stage IV NSCLC survive for five years after diagnosis; more than 50% of patients have stage IV NSCLC at diagnosis.
Why Was This Study Done?
Patient responses to treatment vary considerably. Oncologists (doctors who treat cancer) would like to know which patients have a good prognosis (are likely to do well) to help them individualize their treatment. Consequently, the search is on for “prognostic tumor biomarkers,” molecules made by cancer cells that can be used to predict likely clinical outcomes. Such biomarkers, which may also be potential therapeutic targets, can be identified by analyzing the overall pattern of gene expression in a panel of tumors using a technique called microarray analysis and looking for associations between the expression of sets of genes and clinical outcomes. In this study, the researchers take a more directed approach to identifying prognostic biomarkers by investigating the association between the expression of the genes encoding nuclear receptors (NRs) and clinical outcome in patients with lung cancer. The NR superfamily contains 48 transcription factors (proteins that control the expression of other genes) that respond to several hormones and to diet-derived fats. NRs control many biological processes and are targets for several successful drugs, including some used to treat cancer.
What Did the Researchers Do and Find?
The researchers analyzed the expression of NR mRNAs using “quantitative real-time PCR” in 30 microdissected NSCLCs and in matched normal lung tissue samples (mRNA is the blueprint for protein production). They then used an approach called standard classification and regression tree analysis to build a prognostic model for NSCLC based on the expression data. This model predicted both survival time and disease recurrence among the patients from whom the tumors had been taken. The researchers validated their prognostic model in two large independent lung adenocarcinoma microarray datasets and in a squamous cell carcinoma dataset (adenocarcinomas and squamous cell carcinomas are two major NSCLC subtypes). Finally, they explored the roles of specific NRs in the prediction model. This analysis revealed that the ability of the NR signature in tumors to predict outcomes was mainly due to the expression of two NRs—the short heterodimer partner (SHP) and the progesterone receptor (PR). Expression of either gene could be used as a single gene predictor of the survival time of patients, including those with stage I disease. Similarly, the expression of either nerve growth factor induced gene B3 (NGFIB3) or mineralocorticoid receptor (MR) in normal tissue was a single gene predictor of a good prognosis.
What Do These Findings Mean?
These findings indicate that the expression of NR mRNA is strongly associated with clinical outcomes in patients with NSCLC. Furthermore, they identify a prognostic NR expression signature that provides information on the survival time of patients, including those with early stage disease. The signature needs to be confirmed in more patients before it can be used clinically, and researchers would like to establish whether changes in mRNA expression are reflected in changes in protein expression if NRs are to be targeted therapeutically. Nevertheless, these findings highlight the potential use of NRs as prognostic tumor biomarkers. Furthermore, they identify SHP and PR in tumors and two NRs in normal lung tissue as molecules that might provide new targets for the treatment of lung cancer and new insights into the early diagnosis, pathogenesis, and chemoprevention of lung cancer.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000378.
The Nuclear Receptor Signaling Atlas (NURSA) is consortium of scientists sponsored by the US National Institutes of Health that provides scientific reagents, datasets, and educational material on nuclear receptors and their co-regulators to the scientific community through a Web-based portal
The Cancer Prevention and Research Institute of Texas (CPRIT) provides information and resources to anyone interested in the prevention and treatment of lung and other cancers
The US National Cancer Institute provides detailed information for patients and professionals about all aspects of lung cancer, including information on non-small-cell carcinoma and on tumor markers (in English and Spanish)
Cancer Research UK also provides information about lung cancer and information on how cancer starts
MedlinePlus has links to other resources about lung cancer (in English and Spanish)
Wikipedia has a page on nuclear receptors (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
doi:10.1371/journal.pmed.1000378
PMCID: PMC3001894  PMID: 21179495
13.  A quantitative real-time PCR assay for the identification and enumeration of Alexandrium cysts in marine sediments 
Harmful algal blooms (HABs) are a global problem that affects both human and ecosystem health. One of the most serious and widespread HAB poisoning syndromes is paralytic shellfish poisoning, commonly caused by Alexandrium spp. dinoflagellates. Like many toxic dinoflagellates, Alexandrium produces resistant resting cysts as part of its life cycle. These cysts play a key role in bloom initiation and decline, as well as dispersal and colonization of new areas. Information on cyst numbers and identity is essential for understanding and predicting blooms, yet comprehensive cyst surveys are extremely time- and labor-intensive. Here we describe the development and validation of a quantitative real-time PCR (qPCR) technique for the enumeration of cysts of A. tamarense of the toxic North American/Group I ribotype. The method uses a cloned fragment of the large subunit ribosomal RNA gene as a standard for cyst quantification, with an experimentally determined conversion factor of 28,402±6152 LSU ribosomal gene copies per cyst. Tests of DNA extraction and PCR efficiency show that mechanical breakage is required for adequate cyst lysis, and that it was necessary to dilute our DNA extracts 50-fold in order to abolish PCR inhibition from compounds co-extracted from the sediment. The resulting assay shows a linear response over 6 orders of magnitude and can reliably quantify ≥10cysts/cc sediment.
For method validation, 129 natural sediment samples were split and analyzed in parallel, using both the qPCR and primulin-staining techniques. Overall, there is a significant correlation (p<0.001) between the cyst abundances determined by the two methods, although the qPCR counts tend to be lower than the primulin values. This underestimation is less pronounced in those samples collected from the top 1 cm of sediment, and more pronounced in those derived from the next 1–3 cm of the core. These differences may be due to the condition of the cysts in the different layers, as the top 1cm contains more recent cysts while those in the next 1–3cm may have been in the sediments for many years. Comparison of the cyst densities obtained by both methods shows that a majority (56.6%) of the values are within a two-fold range of each other and almost all of the samples (96.9%) are within an order of magnitude. Thus, the qPCR method described here represents a promising alternative to primulin-staining for the identification and enumeration of cysts. The qPCR method has a higher throughput, enabling the extraction and assay of 24 samples in the time required to process and count 8–10 samples by primulin staining. Both methods require prior expertise, either in taxonomy or molecular biology. Fewer person-hours per sample are required for qPCR, but primulin staining has lower reagent costs. The qPCR method might be more desirable for large-scale cyst mapping, where large numbers of samples are generated and a higher sample analysis rate is necessary. While the qPCR and primulin-staining methods generate similar data, the choice of counting method may be most influenced by the practical issue of the different relative costs of labor and materials between the two methods.
doi:10.1016/j.dsr2.2009.09.006
PMCID: PMC2847306  PMID: 20368759
quantitative PCR; ribosomal; toxic dinoflagellate; saxitoxins; algal blooms; red tides
14.  Reference Genes for Real-Time PCR Quantification of MicroRNAs and Messenger RNAs in Rat Models of Hepatotoxicity 
PLoS ONE  2012;7(5):e36323.
Hepatotoxicity is associated with major changes in liver gene expression induced by xenobiotic exposure. Understanding the underlying mechanisms is critical for its clinical diagnosis and treatment. MicroRNAs are key regulators of gene expression that control mRNA stability and translation, during normal development and pathology. The canonical technique to measure gene transcript levels is Real-Time qPCR, which has been successfully modified to determine the levels of microRNAs as well. However, in order to obtain accurate data in a multi-step method like RT-qPCR, the normalization with endogenous, stably expressed reference genes is mandatory. Since the expression stability of candidate reference genes varies greatly depending on experimental factors, the aim of our study was to identify a combination of genes for optimal normalization of microRNA and mRNA qPCR expression data in experimental models of acute hepatotoxicity. Rats were treated with four traditional hepatotoxins: acetaminophen, carbon tetrachloride, D-galactosamine and thioacetamide, and the liver expression levels of two groups of candidate reference genes, one for microRNA and the other for mRNA normalization, were determined by RT-qPCR in compliance with the MIQE guidelines. In the present study, we report that traditional reference genes such as U6 spliceosomal RNA, Beta Actin and Glyceraldehyde-3P-dehydrogenase altered their expression in response to classic hepatotoxins and therefore cannot be used as reference genes in hepatotoxicity studies. Stability rankings of candidate reference genes, considering only those that did not alter their expression, were determined using geNorm, NormFinder and BestKeeper software packages. The potential candidates whose measurements were stable were further tested in different combinations to find the optimal set of reference genes that accurately determine mRNA and miRNA levels. Finally, the combination of MicroRNA-16/5S Ribosomal RNA and Beta 2 Microglobulin/18S Ribosomal RNA were validated as optimal reference genes for microRNA and mRNA quantification, respectively, in rat models of acute hepatotoxicity.
doi:10.1371/journal.pone.0036323
PMCID: PMC3341372  PMID: 22563491
15.  Reference Gene Selection for qRT-PCR Analysis in the Sweetpotato Whitefly, Bemisia tabaci (Hemiptera: Aleyrodidae) 
PLoS ONE  2013;8(1):e53006.
Background
Accurate evaluation of gene expression requires normalization relative to the expression of reliable reference genes. Expression levels of “classical” reference genes can differ, however, across experimental conditions. Although quantitative real-time PCR (qRT-PCR) has been used extensively to decipher gene function in the sweetpotato whitefly Bemisia tabaci, a world-wide pest in many agricultural systems, the stability of its reference genes has rarely been validated.
Results
In this study, 15 candidate reference genes from B. tabaci were evaluated using two Excel-based algorithms geNorm and Normfinder under a diverse set of biotic and abiotic conditions. At least two reference genes were selected to normalize gene expressions in B. tabaci under experimental conditions. Specifically, for biotic conditions including host plant, acquisition of a plant virus, developmental stage, tissue (body region of the adult), and whitefly biotype, ribosomal protein L29 was the most stable reference gene. In contrast, the expression of elongation factor 1 alpha, peptidylprolyl isomerase A, NADH dehydrogenase, succinate dehydrogenase complex subunit A and heat shock protein 40 were consistently stable across various abiotic conditions including photoperiod, temperature, and insecticide susceptibility.
Conclusion
Our finding is the first step toward establishing a standardized quantitative real-time PCR procedure following the MIQE (Minimum Information for publication of Quantitative real time PCR Experiments) guideline in an agriculturally important insect pest, and provides a solid foundation for future RNA interference based functional study in B. tabaci.
doi:10.1371/journal.pone.0053006
PMCID: PMC3540095  PMID: 23308130
16.  Selection and Evaluation of Potential Reference Genes for Gene Expression Analysis in the Brown Planthopper, Nilaparvata lugens (Hemiptera: Delphacidae) Using Reverse-Transcription Quantitative PCR 
PLoS ONE  2014;9(1):e86503.
The brown planthopper (BPH), Nilaparvata lugens (Hemiptera, Delphacidae), is one of the most important rice pests. Abundant genetic studies on BPH have been conducted using reverse-transcription quantitative real-time PCR (qRT-PCR). Using qRT-PCR, the expression levels of target genes are calculated on the basis of endogenous controls. These genes need to be appropriately selected by experimentally assessing whether they are stably expressed under different conditions. However, such studies on potential reference genes in N. lugens are lacking. In this paper, we presented a systematic exploration of eight candidate reference genes in N. lugens, namely, actin 1 (ACT), muscle actin (MACT), ribosomal protein S11 (RPS11), ribosomal protein S15e (RPS15), alpha 2-tubulin (TUB), elongation factor 1 delta (EF), 18S ribosomal RNA (18S), and arginine kinase (AK) and used four alternative methods (BestKeeper, geNorm, NormFinder, and the delta Ct method) to evaluate the suitability of these genes as endogenous controls. We examined their expression levels among different experimental factors (developmental stage, body part, geographic population, temperature variation, pesticide exposure, diet change, and starvation) following the MIQE (Minimum Information for publication of Quantitative real time PCR Experiments) guidelines. Based on the results of RefFinder, which integrates four currently available major software programs to compare and rank the tested candidate reference genes, RPS15, RPS11, and TUB were found to be the most suitable reference genes in different developmental stages, body parts, and geographic populations, respectively. RPS15 was the most suitable gene under different temperature and diet conditions, while RPS11 was the most suitable gene under different pesticide exposure and starvation conditions. This work sheds light on establishing a standardized qRT-PCR procedure in N. lugens, and serves as a starting point for screening for reference genes for expression studies of related insects.
doi:10.1371/journal.pone.0086503
PMCID: PMC3900570  PMID: 24466124
17.  FlyPrimerBank: An Online Database for Drosophila melanogaster Gene Expression Analysis and Knockdown Evaluation of RNAi Reagents 
G3: Genes|Genomes|Genetics  2013;3(9):1607-1616.
The evaluation of specific endogenous transcript levels is important for understanding transcriptional regulation. More specifically, it is useful for independent confirmation of results obtained by the use of microarray analysis or RNA-seq and for evaluating RNA interference (RNAi)-mediated gene knockdown. Designing specific and effective primers for high-quality, moderate-throughput evaluation of transcript levels, i.e., quantitative, real-time PCR (qPCR), is nontrivial. To meet community needs, predefined qPCR primer pairs for mammalian genes have been designed and sequences made available, e.g., via PrimerBank. In this work, we adapted and refined the algorithms used for the mammalian PrimerBank to design 45,417 primer pairs for 13,860 Drosophila melanogaster genes, with three or more primer pairs per gene. We experimentally validated primer pairs for ~300 randomly selected genes expressed in early Drosophila embryos, using SYBR Green-based qPCR and sequence analysis of products derived from conventional PCR. All relevant information, including primer sequences, isoform specificity, spatial transcript targeting, and any available validation results and/or user feedback, is available from an online database (www.flyrnai.org/flyprimerbank). At FlyPrimerBank, researchers can retrieve primer information for fly genes either one gene at a time or in batch mode. Importantly, we included the overlap of each predicted amplified sequence with RNAi reagents from several public resources, making it possible for researchers to choose primers suitable for knockdown evaluation of RNAi reagents (i.e., to avoid amplification of the RNAi reagent itself). We demonstrate the utility of this resource for validation of RNAi reagents in vivo.
doi:10.1534/g3.113.007021
PMCID: PMC3755921  PMID: 23893746
Drosophila; real-time PCR; gene expression; RNAi; knockdown evaluation
18.  Careful Selection of Reference Genes Is Required for Reliable Performance of RT-qPCR in Human Normal and Cancer Cell Lines 
PLoS ONE  2013;8(3):e59180.
Reverse Transcription - quantitative Polymerase Chain Reaction (RT-qPCR) is a standard technique in most laboratories. The selection of reference genes is essential for data normalization and the selection of suitable reference genes remains critical. Our aim was to 1) review the literature since implementation of the MIQE guidelines in order to identify the degree of acceptance; 2) compare various algorithms in their expression stability; 3) identify a set of suitable and most reliable reference genes for a variety of human cancer cell lines. A PubMed database review was performed and publications since 2009 were selected. Twelve putative reference genes were profiled in normal and various cancer cell lines (n = 25) using 2-step RT-qPCR. Investigated reference genes were ranked according to their expression stability by five algorithms (geNorm, Normfinder, BestKeeper, comparative ΔCt, and RefFinder). Our review revealed 37 publications, with two thirds patient samples and one third cell lines. qPCR efficiency was given in 68.4% of all publications, but only 28.9% of all studies provided RNA/cDNA amount and standard curves. GeNorm and Normfinder algorithms were used in 60.5% in combination. In our selection of 25 cancer cell lines, we identified HSPCB, RRN18S, and RPS13 as the most stable expressed reference genes. In the subset of ovarian cancer cell lines, the reference genes were PPIA, RPS13 and SDHA, clearly demonstrating the necessity to select genes depending on the research focus. Moreover, a cohort of at least three suitable reference genes needs to be established in advance to the experiments, according to the guidelines. For establishing a set of reference genes for gene normalization we recommend the use of ideally three reference genes selected by at least three stability algorithms. The unfortunate lack of compliance to the MIQE guidelines reflects that these need to be further established in the research community.
doi:10.1371/journal.pone.0059180
PMCID: PMC3598660  PMID: 23554992
19.  Standardisation of data from real-time quantitative PCR methods – evaluation of outliers and comparison of calibration curves 
BMC Biotechnology  2005;5:31.
Background
As real-time quantitative PCR (RT-QPCR) is increasingly being relied upon for the enforcement of legislation and regulations dependent upon the trace detection of DNA, focus has increased on the quality issues related to the technique. Recent work has focused on the identification of factors that contribute towards significant measurement uncertainty in the real-time quantitative PCR technique, through investigation of the experimental design and operating procedure. However, measurement uncertainty contributions made during the data analysis procedure have not been studied in detail. This paper presents two additional approaches for standardising data analysis through the novel application of statistical methods to RT-QPCR, in order to minimise potential uncertainty in results.
Results
Experimental data was generated in order to develop the two aspects of data handling and analysis that can contribute towards measurement uncertainty in results. This paper describes preliminary aspects in standardising data through the application of statistical techniques to the area of RT-QPCR. The first aspect concerns the statistical identification and subsequent handling of outlying values arising from RT-QPCR, and discusses the implementation of ISO guidelines in relation to acceptance or rejection of outlying values. The second aspect relates to the development of an objective statistical test for the comparison of calibration curves.
Conclusion
The preliminary statistical tests for outlying values and comparisons between calibration curves can be applied using basic functions found in standard spreadsheet software. These two aspects emphasise that the comparability of results arising from RT-QPCR needs further refinement and development at the data-handling phase. The implementation of standardised approaches to data analysis should further help minimise variation due to subjective judgements. The aspects described in this paper will help contribute towards the development of a set of best practice guidelines regarding standardising handling and interpretation of data arising from RT-QPCR experiments.
doi:10.1186/1472-6750-5-31
PMCID: PMC1326201  PMID: 16336641
20.  MIQE précis: Practical implementation of minimum standard guidelines for fluorescence-based quantitative real-time PCR experiments 
BMC Molecular Biology  2010;11:74.
The conclusions of thousands of peer-reviewed publications rely on data obtained using fluorescence-based quantitative real-time PCR technology. However, the inadequate reporting of experimental detail, combined with the frequent use of flawed protocols is leading to the publication of papers that may not be technically appropriate. We take the view that this problem requires the delineation of a more transparent and comprehensive reporting policy from scientific journals. This editorial aims to provide practical guidance for the incorporation of absolute minimum standards encompassing the key assay parameters for accurate design, documentation and reporting of qPCR experiments (MIQE précis) and guidance on the publication of pure 'reference gene' articles.
doi:10.1186/1471-2199-11-74
PMCID: PMC2955025  PMID: 20858237
21.  Construction of a nasopharyngeal carcinoma 2D/MS repository with Open Source XML Database – Xindice 
Background
Many proteomics initiatives require integration of all information with uniformcriteria from collection of samples and data display to publication of experimental results. The integration and exchanging of these data of different formats and structure imposes a great challenge to us. The XML technology presents a promise in handling this task due to its simplicity and flexibility. Nasopharyngeal carcinoma (NPC) is one of the most common cancers in southern China and Southeast Asia, which has marked geographic and racial differences in incidence. Although there are some cancer proteome databases now, there is still no NPC proteome database.
Results
The raw NPC proteome experiment data were captured into one XML document with Human Proteome Markup Language (HUP-ML) editor and imported into native XML database Xindice. The 2D/MS repository of NPC proteome was constructed with Apache, PHP and Xindice to provide access to the database via Internet. On our website, two methods, keyword query and click query, were provided at the same time to access the entries of the NPC proteome database.
Conclusion
Our 2D/MS repository can be used to share the raw NPC proteomics data that are generated from gel-based proteomics experiments. The database, as well as the PHP source codes for constructing users' own proteome repository, can be accessed at .
doi:10.1186/1471-2105-7-13
PMCID: PMC1351203  PMID: 16403238
22.  How to perform RT-qPCR accurately in plant species? A case study on flower colour gene expression in an azalea (Rhododendron simsii hybrids) mapping population 
BMC Molecular Biology  2013;14:13.
Background
Flower colour variation is one of the most crucial selection criteria in the breeding of a flowering pot plant, as is also the case for azalea (Rhododendron simsii hybrids). Flavonoid biosynthesis was studied intensively in several species. In azalea, flower colour can be described by means of a 3-gene model. However, this model does not clarify pink-coloration. The last decade gene expression studies have been implemented widely for studying flower colour. However, the methods used were often only semi-quantitative or quantification was not done according to the MIQE-guidelines. We aimed to develop an accurate protocol for RT-qPCR and to validate the protocol to study flower colour in an azalea mapping population.
Results
An accurate RT-qPCR protocol had to be established. RNA quality was evaluated in a combined approach by means of different techniques e.g. SPUD-assay and Experion-analysis. We demonstrated the importance of testing noRT-samples for all genes under study to detect contaminating DNA. In spite of the limited sequence information available, we prepared a set of 11 reference genes which was validated in flower petals; a combination of three reference genes was most optimal. Finally we also used plasmids for the construction of standard curves. This allowed us to calculate gene-specific PCR efficiencies for every gene to assure an accurate quantification. The validity of the protocol was demonstrated by means of the study of six genes of the flavonoid biosynthesis pathway. No correlations were found between flower colour and the individual expression profiles. However, the combination of early pathway genes (CHS, F3H, F3'H and FLS) is clearly related to co-pigmentation with flavonols. The late pathway genes DFR and ANS are to a minor extent involved in differentiating between coloured and white flowers. Concerning pink coloration, we could demonstrate that the lower intensity in this type of flowers is correlated to the expression of F3'H.
Conclusions
Currently in plant research, validated and qualitative RT-qPCR protocols are still rare. The protocol in this study can be implemented on all plant species to assure accurate quantification of gene expression. We have been able to correlate flower colour to the combined regulation of structural genes, both in the early and late branch of the pathway. This allowed us to differentiate between flower colours in a broader genetic background as was done so far in flower colour studies. These data will now be used for eQTL mapping to comprehend even more the regulation of this pathway.
doi:10.1186/1471-2199-14-13
PMCID: PMC3698002  PMID: 23800303
RT-qPCR; Flower colour; RNA quality; noRT; Standard curves; Reference genes; Gene expression; Pink
23.  The kSORT Assay to Detect Renal Transplant Patients at High Risk for Acute Rejection: Results of the Multicenter AART Study 
PLoS Medicine  2014;11(11):e1001759.
Minnie Sarwal and colleagues developed a gene expression assay using peripheral blood samples to detect patients with renal transplant at high risk for acute rejection.
Please see later in the article for the Editors' Summary
Background
Development of noninvasive molecular assays to improve disease diagnosis and patient monitoring is a critical need. In renal transplantation, acute rejection (AR) increases the risk for chronic graft injury and failure. Noninvasive diagnostic assays to improve current late and nonspecific diagnosis of rejection are needed. We sought to develop a test using a simple blood gene expression assay to detect patients at high risk for AR.
Methods and Findings
We developed a novel correlation-based algorithm by step-wise analysis of gene expression data in 558 blood samples from 436 renal transplant patients collected across eight transplant centers in the US, Mexico, and Spain between 5 February 2005 and 15 December 2012 in the Assessment of Acute Rejection in Renal Transplantation (AART) study. Gene expression was assessed by quantitative real-time PCR (QPCR) in one center. A 17-gene set—the Kidney Solid Organ Response Test (kSORT)—was selected in 143 samples for AR classification using discriminant analysis (area under the receiver operating characteristic curve [AUC] = 0.94; 95% CI 0.91–0.98), validated in 124 independent samples (AUC = 0.95; 95% CI 0.88–1.0) and evaluated for AR prediction in 191 serial samples, where it predicted AR up to 3 mo prior to detection by the current gold standard (biopsy). A novel reference-based algorithm (using 13 12-gene models) was developed in 100 independent samples to provide a numerical AR risk score, to classify patients as high risk versus low risk for AR. kSORT was able to detect AR in blood independent of age, time post-transplantation, and sample source without additional data normalization; AUC = 0.93 (95% CI 0.86–0.99). Further validation of kSORT is planned in prospective clinical observational and interventional trials.
Conclusions
The kSORT blood QPCR assay is a noninvasive tool to detect high risk of AR of renal transplants.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Throughout life, the kidneys filter waste products (from the normal breakdown of tissues and food) and excess water from the blood to make urine. If the kidneys stop working for any reason, the rate at which the blood is filtered decreases, and dangerous amounts of creatinine and other waste products build up in the blood. The kidneys can fail suddenly (acute kidney failure) because of injury or poisoning, but usually failing kidneys stop working gradually over many years (chronic kidney disease). Chronic kidney disease is very common, especially in people who have high blood pressure or diabetes and in elderly people. In the UK, for example, about 20% of people aged 65–74 years have some degree of chronic kidney disease. People whose kidneys fail completely (end-stage kidney disease) need regular dialysis (hemodialysis, in which blood is filtered by an external machine, or peritoneal dialysis, which uses blood vessels in the abdominal lining to do the work of the kidneys) or a renal transplant (the surgical transfer of a healthy kidney from another person into the patient's body) to keep them alive.
Why Was This Study Done?
Our immune system protects us from pathogens (disease-causing organisms) by recognizing specific molecules (antigens) on the invader's surface as foreign and initiating a sequence of events that kills the invader. Unfortunately, the immune system sometimes recognizes kidney transplants as foreign and triggers transplant rejection. The chances of rejection can be minimized by “matching” the antigens on the donated kidney to those on the tissues of the kidney recipient and by giving the recipient immunosuppressive drugs. However, acute rejection (rejection during the first year after transplantation) affects about 20% of kidney transplants. Acute rejection needs to be detected quickly and treated with a short course of more powerful immunosuppressants because it increases the risk of transplant failure. The current “gold standard” method for detecting acute rejection if the level of creatinine in the patient's blood begins to rise is to surgically remove a small piece (biopsy) of the transplanted kidney for analysis. However, other conditions can change creatinine levels, acute rejection can occur without creatinine levels changing (subclinical acute rejection), and biopsies are invasive. Here, the researchers develop a noninvasive test for acute kidney rejection called the Kidney Solid Organ Response Test (kSORT) based on gene expression levels in the blood.
What Did the Researchers Do and Find?
For the Assessment of Acute Rejection in Renal Transplantation (AART) study, the researchers used an assay called quantitative polymerase chain reaction (QPCR) to measure the expression of 43 genes whose expression levels change during acute kidney rejection in blood samples collected from patients who had had a kidney transplant. Using a training set of 143 samples and statistical analyses, the researchers identified a 17-gene set (kSORT) that discriminated between patients with and without acute rejection detected by kidney biopsy. The 17-gene set correctly identified 39 of the samples taken from 47 patients with acute rejection as being from patients with acute rejection, and 87 of 96 samples from patients without acute rejection as being from patients without acute rejection. The researchers validated the gene set using 124 independent samples. Then, using 191 serial samples, they showed that the gene set was able to predict acute rejection up to three months before detection by biopsy. Finally, the researchers used 100 blood samples to develop an algorithm (a step-wise calculation) to classify patients as being at high or low risk of acute rejection.
What Do These Findings Mean?
These findings describe the early development of a noninvasive tool (kSORT) that might, eventually, help clinicians identify patients at risk of acute rejection after kidney transplantation. kSORT needs to be tested in more patients before being used clinically, however, to validate its predictive ability, particularly given that the current gold standard test against which it was compared (biopsy) is far from perfect. An additional limitation of kSORT is that it did not discriminate between cell-mediated and antibody-mediated immune rejection. These two types of immune rejection are treated in different ways, so clinicians ideally need a test for acute rejection that indicates which form of immune rejection is involved. The authors are conducting a follow-up study to help determine whether kSORT can be used in clinical practice to identify acute rejection and to identify which patients are at greatest risk of transplant rejection and may require biopsy.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001759.
The US National Kidney and Urologic Diseases Information Clearinghouse provides links to information about all aspects of kidney disease; the US National Kidney Disease Education Program provides resources to help improve the understanding, detection, and management of kidney disease (in English and Spanish)
The UK National Health Service Choices website provides information for patients on chronic kidney disease and about kidney transplants, including some personal stories
The US National Kidney Foundation, a not-for-profit organization, provides information about chronic kidney disease and about kidney transplantation (in English and Spanish)
The not-for-profit UK National Kidney Federation provides support and information for patients with kidney disease and for their carers, including information and personal stories about kidney donation and transplantation
World Kidney Day, a joint initiative between the International Society of Nephrology and the International Federation of Kidney Foundations, aims to raise awareness about kidneys and kidney disease
MedlinePlus provides links to additional resources about kidney diseases, kidney failure, and kidney transplantation; the MedlinePlus encyclopedia has a page about transplant rejection
doi:10.1371/journal.pmed.1001759
PMCID: PMC4227654  PMID: 25386950
24.  High-Throughput Direct Fecal PCR Assay for Detection of Mycobacterium avium subsp. paratuberculosis in Sheep and Cattle 
Journal of Clinical Microbiology  2014;52(3):745-757.
Johne's disease (JD) is a chronic enteric disease caused by Mycobacterium avium subsp. paratuberculosis that affects ruminants. Transmission occurs by the fecal-oral route. A commonly used antemortem diagnostic test for the detection of M. avium subsp. paratuberculosis in feces is liquid culture; however, a major constraint is the 2- to 3-month incubation period needed for this method. Rapid methods for the detection of M. avium subsp. paratuberculosis based on PCR have been reported, but comprehensive validation data are lacking. We describe here a new test, the high-throughput-Johnes (HT-J), to detect M. avium subsp. paratuberculosis in feces. Its diagnostic accuracy was compared with that of liquid radiometric (Bactec) fecal culture using samples from cattle (1,330 samples from 23 herds) and sheep (596 samples from 16 flocks). The multistage protocol involves the recovery of M. avium subsp. paratuberculosis cells from a fecal suspension, cell rupture by bead beating, extraction of DNA using magnetic beads, and IS900 quantitative PCR. The limit of detection of the assay was 0.0005 pg, and the limit of quantification was 0.005 pg M. avium subsp. paratuberculosis genomic DNA. Only M. avium subsp. paratuberculosis was detected from a panel of 51 mycobacterial isolates, including 10 with IS900-like sequences. Of the 549 culture-negative fecal samples from unexposed herds and flocks, 99% were negative in the HT-J test, while 60% of the bovine- and 84% of the ovine-culture-positive samples were positive in the HT-J test. As similar total numbers of samples from M. avium subsp. paratuberculosis-exposed animals were positive in culture and HT-J tests in both species, and as the results of a McNemar's test were not significant, these methods probably have similar sensitivities, but the true diagnostic sensitivities of these tests are unknown. These validation data meet the consensus-based reporting standards for diagnostic test accuracy studies for paratuberculosis and the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines (S. A. Bustin et al., Clin. Chem. 55:611–622, 2009, doi:10.1373/clinchem.2008.112797). The HT-J assay has been approved for use in JD control programs in Australia and New Zealand.
doi:10.1128/JCM.03233-13
PMCID: PMC3957769  PMID: 24352996
25.  Evidence for the Selective Reporting of Analyses and Discrepancies in Clinical Trials: A Systematic Review of Cohort Studies of Clinical Trials 
PLoS Medicine  2014;11(6):e1001666.
In a systematic review of cohort studies, Kerry Dwan and colleagues examine the evidence for selective reporting and discrepancies in analyses between journal publications and other documents for clinical trials.
Please see later in the article for the Editors' Summary
Background
Most publications about selective reporting in clinical trials have focussed on outcomes. However, selective reporting of analyses for a given outcome may also affect the validity of findings. If analyses are selected on the basis of the results, reporting bias may occur. The aims of this study were to review and summarise the evidence from empirical cohort studies that assessed discrepant or selective reporting of analyses in randomised controlled trials (RCTs).
Methods and Findings
A systematic review was conducted and included cohort studies that assessed any aspect of the reporting of analyses of RCTs by comparing different trial documents, e.g., protocol compared to trial report, or different sections within a trial publication. The Cochrane Methodology Register, Medline (Ovid), PsycInfo (Ovid), and PubMed were searched on 5 February 2014. Two authors independently selected studies, performed data extraction, and assessed the methodological quality of the eligible studies. Twenty-two studies (containing 3,140 RCTs) published between 2000 and 2013 were included. Twenty-two studies reported on discrepancies between information given in different sources. Discrepancies were found in statistical analyses (eight studies), composite outcomes (one study), the handling of missing data (three studies), unadjusted versus adjusted analyses (three studies), handling of continuous data (three studies), and subgroup analyses (12 studies). Discrepancy rates varied, ranging from 7% (3/42) to 88% (7/8) in statistical analyses, 46% (36/79) to 82% (23/28) in adjusted versus unadjusted analyses, and 61% (11/18) to 100% (25/25) in subgroup analyses. This review is limited in that none of the included studies investigated the evidence for bias resulting from selective reporting of analyses. It was not possible to combine studies to provide overall summary estimates, and so the results of studies are discussed narratively.
Conclusions
Discrepancies in analyses between publications and other study documentation were common, but reasons for these discrepancies were not discussed in the trial reports. To ensure transparency, protocols and statistical analysis plans need to be published, and investigators should adhere to these or explain discrepancies.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
In the past, clinicians relied on their own experience when choosing the best treatment for their patients. Nowadays, they turn to evidence-based medicine—the systematic review and appraisal of trials, studies that investigate the benefits and harms of medical treatments in patients. However, evidence-based medicine can guide clinicians only if all the results from clinical trials are published in an unbiased and timely manner. Unfortunately, the results of trials in which a new drug performs better than existing drugs are more likely to be published than those in which the new drug performs badly or has unwanted side effects (publication bias). Moreover, trial outcomes that support the use of a new treatment are more likely to be published than those that do not support its use (outcome reporting bias). Recent initiatives—such as making registration of clinical trials in a trial registry (for example, ClinicalTrials.gov) a prerequisite for publication in medical journals—aim to prevent these biases, which pose a threat to informed medical decision-making.
Why Was This Study Done?
Selective reporting of analyses of outcomes may also affect the validity of clinical trial findings. Sometimes, for example, a trial publication will include a per protocol analysis (which considers only the outcomes of patients who received their assigned treatment) rather than a pre-planned intention-to-treat analysis (which considers the outcomes of all the patients regardless of whether they received their assigned treatment). If the decision to publish the per protocol analysis is based on the results of this analysis being more favorable than those of the intention-to-treat analysis (which more closely resembles “real” life), then “analysis reporting bias” has occurred. In this systematic review, the researchers investigate the selective reporting of analyses and discrepancies in randomized controlled trials (RCTs) by reviewing published studies that assessed selective reporting of analyses in groups (cohorts) of RCTs and discrepancies in analyses of RCTs between different sources (for example, between the protocol in a trial registry and the journal publication) or different sections of a source. A systematic review uses predefined criteria to identify all the research on a given topic.
What Did the Researchers Do and Find?
The researchers identified 22 cohort studies (containing 3,140 RCTs) that were eligible for inclusion in their systematic review. All of these studies reported on discrepancies between the information provided by the RCTs in different places, but none investigated the evidence for analysis reporting bias. Several of the cohort studies reported, for example, that there were discrepancies in the statistical analyses included in the different documents associated with the RCTs included in their analysis. Other types of discrepancies reported by the cohort studies included discrepancies in the reporting of composite outcomes (an outcome in which multiple end points are combined) and in the reporting of subgroup analyses (investigations of outcomes in subgroups of patients that should be predefined in the trial protocol to avoid bias). Discrepancy rates varied among the RCTs according to the types of analyses and cohort studies considered. Thus, whereas in one cohort study discrepancies were present in the statistical test used for the analysis of the primary outcome in only 7% of the included studies, they were present in the subgroup analyses of all the included studies.
What Do These Findings Mean?
These findings indicate that discrepancies in analyses between publications and other study documents such as protocols in trial registries are common. The reasons for these discrepancies in analyses were not discussed in trial reports but may be the result of reporting bias, errors, or legitimate departures from a pre-specified protocol. For example, a statistical analysis that is not specified in the trial protocol may sometimes appear in a publication because the journal requested its inclusion as a condition of publication. The researchers suggest that it may be impossible for systematic reviewers to distinguish between these possibilities simply by looking at the source documentation. Instead, they suggest, it may be necessary for reviewers to contact the trial authors. However, to make selective reporting of analyses more easily detectable, they suggest that protocols and analysis plans should be published and that investigators should be required to stick to these plans or explain any discrepancies when they publish their trial results. Together with other initiatives, this approach should help improve the quality of evidence-based medicine and, as a result, the treatment of patients.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001666.
Wikipedia has pages on evidence-based medicine, on systematic reviews, and on publication bias (note: Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
ClinicalTrials.gov provides information about the US National Institutes of Health clinical trial registry, including background information about clinical trials
The Cochrane Collaboration is a global independent network of health practitioners, researchers, patient advocates, and others that aims to promote evidence-informed health decision-making by producing high-quality, relevant, accessible systematic reviews and other synthesized research evidence; the Cochrane Handbook for Systematic Reviews of Interventions describes the preparation of systematic reviews in detail
PLOS Medicine recently launched a Reporting Guidelines Collection, an open-access collection of reporting guidelines, commentary, and related research on guidelines from across PLOS journals that aims to help advance the efficiency, effectiveness, and equitability of the dissemination of biomedical information
doi:10.1371/journal.pmed.1001666
PMCID: PMC4068996  PMID: 24959719

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