The reproducibility of biomedical research: Sleepers awake!

Experimental reporting of fish transcriptomic responses in environmental toxicology and ecotoxicology

Due to its increasing affordability and efforts to understand transcriptional responses of organisms to biotic and abiotic stimuli, transcriptomics has become an important tool with significant impact on toxicological investigations and hazard and risk assessments, especially during development and application of new approach methodologies (NAMs). Data generated using transcriptomic methodologies have directly informed adverse outcome pathway frameworks, chemical and biological read across, and aided in the identification of points of departure. Using data reporting frameworks for transcriptomics data offers improved transparency and reproducibility of research and an opportunity to identify barriers to adoption of these NAMs, especially in environmental toxicology and ecotoxicology with aquatic models. Improved reporting also allows for reexamination of existing data, limiting needs for experiment replication and further reducing animal experimentation. Here, we use a standardized form of data reporting for omics-based studies, the Organisation for Economic Co-operation and Development omics reporting framework, which specifically reports on a list of parameters that should be included in transcriptomics studies used in a regulatory context. We focused specifically on fish studies using RNA- Sequencing (Seq)/microarray technologies within a toxicology context. Inconsistencies in reporting and methodologies among the experimental designs (toxicology vs. molecular characterization) were observed in addition to foundational differences in reporting of sample concentration or preparation or quality assessments, which can affect reproducibility and read across, confidence in results, and contribute substantially to understanding molecular mechanisms of toxicants and toxins. Our findings present an opportunity for improved research reporting. We also provide several recommendations as logical steps to reduce barriers to adoption of transcriptomics within environmental toxicology and ecotoxicology.

Evaluation of variation in preclinical electroencephalographic (EEG) spectral power across multiple laboratories and experiments: An EQIPD study

The European Quality In Preclinical Data (EQIPD) consortium was born from the fact that publications report challenges with the robustness, rigor, and/or validity of research data, which may impact decisions about whether to proceed with further preclinical testing or to advance to clinical testing, as well as draw conclusions on the predictability of preclinical models. To address this, a consortium including multiple research laboratories from academia and industry participated in a series of electroencephalography (EEG) experiments in mice aimed to detect sources of variance and to gauge how protocol harmonisation and data analytics impact such variance. Ultimately, the goal of this first ever between-laboratory comparison of EEG recordings and analyses was to validate the principles that supposedly increase data quality, robustness, and comparability. Experiments consisted of a Localisation phase, which aimed to identify the factors that influence between-laboratory variability, a Harmonisation phase to evaluate whether harmonisation of standardized protocols and centralised processing and data analysis reduced variance, and a Ring-Testing phase to verify the ability of the harmonised protocol to generate consistent findings. Indeed, between-laboratory variability reduced from Localisation to Harmonisation and this reduction remained during the Ring-Testing phase. Results obtained in this multicentre preclinical qEEG study also confirmed the complex nature of EEG experiments starting from the surgery and data collection through data pre-processing to data analysis that ultimately influenced the results and contributed to variance in findings across laboratories. Overall, harmonisation of protocols and centralized data analysis were crucial in reducing laboratory-to-laboratory variability. To this end, it is recommended that standardized guidelines be updated and followed for collection and analysis of preclinical EEG data.

A Strategy for the Selection of RT-qPCR Reference Genes Based on Publicly Available Transcriptomic Datasets

In the next-generation sequencing era, RT-qPCR is still widely employed to quantify levels of nucleic acids of interest due to its popularity, versatility, and limited costs. The measurement of transcriptional levels through RT-qPCR critically depends on reference genes used for normalization. Here, we devised a strategy to select appropriate reference genes for a specific clinical/experimental setting based on publicly available transcriptomic datasets and a pipeline for RT-qPCR assay design and validation. As a proof-of-principle, we applied this strategy to identify and validate reference genes for transcriptional studies of bone-marrow plasma cells from patients with AL amyloidosis. We performed a systematic review of published literature to compile a list of 163 candidate reference genes for RT-qPCR experiments employing human samples. Next, we interrogated the Gene Expression Omnibus to assess expression levels of these genes in published transcriptomic studies on bone-marrow plasma cells from patients with different plasma cell dyscrasias and identified the most stably expressed genes as candidate normalizing genes. Experimental validation on bone-marrow plasma cells showed the superiority of candidate reference genes identified through this strategy over commonly employed "housekeeping" genes. The strategy presented here may apply to other clinical and experimental settings for which publicly available transcriptomic datasets are available.

Rigor, Reproducibility, and Transparency in Shared Research Resources: Follow-Up Survey and Recommendations for Improvements

Rigor, reproducibility, and transparency (RR&T) are essential components of all scientific pursuits. Shared research resources, also known as core facilities, are on the frontlines of ensuring robust RR&T practices. The Association of Biomolecular Resource Facilities Committee on Core Rigor and Reproducibility conducted a follow-up survey 4 years after the initial 2017 survey to determine if core facilities have seen a positive impact of new RR&T initiatives (including guidance from the National Institutes of Health, new scientific journal requirements on transparency and data provenance, and educational tools from professional organizations). While there were fewer participants in the most recent survey, the respondents' opinions on the role of core facilities and level of best practices adoption remained the same. Overall, the respondents agreed that procedures should be implemented by core facilities to ensure scientific RR&T. They also indicated that there is a strong correlation between institutions that emphasize RR&T and core customers using this expertise in grant applications and publications. The survey also assessed the impact of the COVID-19 pandemic on core operations and RR&T. The answers to these pandemic-related questions revealed that many of the strategies aimed at increasing efficiencies are also best practices related to RR&T, including the development of standard operating procedures, supply chain management, and cross training. Given the consistent and compelling awareness of the importance of RR&T expressed by core directors in 2017 and 2021 contrasted with the lack of apparent improvements over this time period, the authors recommend an adoption of RR&T statements by all core laboratories. Adhering to the RR&T guidelines will result in more efficient training, better compliance, and improved experimental approaches empowering cores to become "rigor champions."

CRISPR-Cas, Argonaute proteins and the emerging landscape of amplification-free diagnostics

Polymerase Chain Reaction (PCR) is the reigning gold standard for molecular diagnostics. However, the SARS-CoV-2 pandemic reveals an urgent need for new diagnostics that provide users with immediate results without complex procedures or sophisticated equipment. These new demands have stimulated a tsunami of innovations that improve turnaround times without compromising the specificity and sensitivity that has established PCR as the paragon of diagnostics. Here we briefly introduce the origins of PCR and isothermal amplification, before turning to the emergence of CRISPR-Cas and Argonaute proteins, which are being coupled to fluorimeters, spectrometers, microfluidic devices, field-effect transistors, and amperometric biosensors, for a new generation of nucleic acid-based diagnostics.

Application of a High-Throughput Targeted Sequence AmpliSeq Procedure to Assess the Presence and Variants of Virulence Genes in Salmonella

We have developed a targeted, amplicon-based next-generation sequencing method to detect and analyze 227 virulence genes (VG) of Salmonella (AmpliSeq_{Salm_227VG}) for assessing the pathogenicity potential of Salmonella. The procedure was developed using 80 reference genomes representing 75 epidemiologically-relevant serovars associated with human salmonellosis. We applied the AmpliSeq_{Salm_227VG} assay to (a) 35 previously characterized field strains of Salmonella consisting of serovars commonly incriminated in foodborne illnesses and (b) 34 Salmonella strains with undisclosed serological or virulence attributes, and were able to divide Salmonella VGs into two groups: core VGs and variable VGs. The commonest serovars causing foodborne illnesses such as Enteritidis, Typhimurium, Heidelberg and Newport had a high number of VGs (217–227). In contrast, serovars of subspecies not commonly associated with human illnesses, such as houtenae, arizonae and salame, tended to have fewer VGs (177–195). Variable VGs were not only infrequent but, when present, displayed considerable sequence variation: safC, sseL, sseD, sseE, ssaK and stdB showed the highest variation and were linked to strain pathogenicity. In a chicken infection model, VGs belonging to rfb and sse operons showed differences and were linked with pathogenicity. The high-throughput, targeted NGS-based AmpliSeq_{Salm_227VG} procedure provided previously unknown information about variation in select virulence genes that can now be applied to a much larger population of Salmonella for evaluating pathogenicity of various serovars of Salmonella and for risk assessment of foodborne salmonellosis.

Upregulation of circular and linear METTL3 and USP3 in colorectal cancer

Several screening methods are currently used to detect colorectal cancer (CRC). However, these are either under-utilized due to their invasive nature or are limited in terms of their diagnostic ability. Numerous reports have investigated messenger and circular RNA as non-invasive biomarkers, but the majority of gene expression studies using RT-qPCR involve critical errors that often lead to irreproducible findings. In the present study, several of these issues were addressed. To the best of our knowledge, this study reports for the first time the upregulation of both the circular and the linear isoform of USP3 and METTL3 in leukocytes from patients with CRC. The linear transcripts of USP3 and METTL3 exhibited 2.3- and 2-fold increases on average in CRC samples (n=42 CRC) compared with the respective healthy controls (n=32), whereas their circular isoforms showed 1.6- and 1.7-fold increases, respectively. Moreover, a strong positive correlation was observed between the circular and linear isoforms of USP3 in the CRC cohort (P<0.0001), but not in the control group (P>0.05). In addition, the linear USP3 assay had excellent sensitivity (79%), specificity (75%), positive predictive value (81%), negative predictive value (73%) and area under the curve (AUC, 0.8534; P-value <0.0001). The circular (AUC, 0.6946; P-value =0.0043) and linear (AUC, 0.7202; P-value =0.0012) METTL3 assays also showed potential; however, this was not the case for the circular USP3 assay (P-value >0.05). Taken together, this stringent RT-qPCR approach provides evidence for the viability of using circular and linear RNA molecules as disease biomarkers and may help shed light on the regulatory pathways of CRC.

An adaptable dry lab for SYBR based RT-qPCR primer design to reinforce concepts in molecular biology and nucleic acids

The real time PCR (qPCR) method provides a powerful method to assess levels of particular species of DNA. When combined with reverse transcription (RT-qPCR) it is the predominate technique to measure expression of gene transcripts. While this approach is very powerful, particular care must be taken in the design of the primers to facilitate specific and sensitive detection. Herein describes the framework for an undergraduate assignment which aims to teach primer design for SYBR based RT-qPCR. Beyond gaining direct experience with primer design, students will gain familiarity with important bioinformatic resources as well as a deeper theoretical understanding of the RT-qPCR approach and potential limitations. Moreover, as students' progress through the assignment they re-encounter many important concepts in molecular biology, gene expression, and nucleic acids, creating an opportunity for spiral learning. As this exercise only requires access to free web-based resources and does not require a laboratory it can be used in most science education settings. Despite not being a wet lab, this is a highly authentic research experience as this design process is commonplace in a molecular biology laboratory. Furthermore, the assignment is highly adaptable for different learning outcomes, time frames, and student background and ability. This article seeks to highlight connections and expanded learning outcomes for those already teaching such material, as well as a step-by-step guide for those new to teaching such content.

COVID-19 and Diagnostic Testing for SARS-CoV-2 by RT-qPCR-Facts and Fallacies

Although molecular testing, and RT-qPCR in particular, has been an indispensable component in the scientific armoury targeting SARS-CoV-2, there are numerous falsehoods, misconceptions, assumptions and exaggerated expectations with regards to capability, performance and usefulness of the technology. It is essential that the true strengths and limitations, although publicised for at least twenty years, are restated in the context of the current COVID-19 epidemic. The main objective of this commentary is to address and help stop the unfounded and debilitating speculation surrounding its use.

The Impact of Acute Loud Noise on the Behavior of Laboratory Birds

Husbandry procedures and facility settings, such as low-frequency fire alarms, can produce noises in a laboratory environment that cause stress to animals used in research. However, most of the data demonstrating harmful effects that have, consequently, led to adaptations to management, have largely come from laboratory rodents with little known of the impacts on avian behavior and physiology. Here we examined whether exposure to a routine laboratory noise, a low-frequency fire alarm test, induced behavioral changes in laboratory zebra finches (Taeniopygia guttata). Twenty-four breeding pairs of zebra finches were randomly selected and exposed to the low-frequency fire alarm (sounding for 10-20 s) or no noise (control) on separate test days. All birds were filmed before and after the alarm sounded and on a control day (without the alarm). The zebra finches decreased their general activity and increased stationary and social behaviors after exposure to the alarm. Brief exposure to a low-frequency alarm disrupted the birds' behavior for at least 15 min. The induction of this behavioral stress response suggests that low-frequency sound alarms in laboratory facilities have the potential to compromise the welfare of laboratory birds.

Prospects and challenges of multi-omics data integration in toxicology

Exposure of cells or organisms to chemicals can trigger a series of effects at the regulatory pathway level, which involve changes of levels, interactions, and feedback loops of biomolecules of different types. A single-omics technique, e.g., transcriptomics, will detect biomolecules of one type and thus can only capture changes in a small subset of the biological cascade. Therefore, although applying single-omics analyses can lead to the identification of biomarkers for certain exposures, they cannot provide a systemic understanding of toxicity pathways or adverse outcome pathways. Integration of multiple omics data sets promises a substantial improvement in detecting this pathway response to a toxicant, by an increase of information as such and especially by a systemic understanding. Here, we report the findings of a thorough evaluation of the prospects and challenges of multi-omics data integration in toxicological research. We review the availability of such data, discuss options for experimental design, evaluate methods for integration and analysis of multi-omics data, discuss best practices, and identify knowledge gaps. Re-analyzing published data, we demonstrate that multi-omics data integration can considerably improve the confidence in detecting a pathway response. Finally, we argue that more data need to be generated from studies with a multi-omics-focused design, to define which omics layers contribute most to the identification of a pathway response to a toxicant.

A resting state fMRI analysis pipeline for pooling inference across diverse cohorts: an ENIGMA rs-fMRI protocol

Large-scale consortium efforts such as Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) and other collaborative efforts show that combining statistical data from multiple independent studies can boost statistical power and achieve more accurate estimates of effect sizes, contributing to more reliable and reproducible research. A meta- analysis would pool effects from studies conducted in a similar manner, yet to date, no such harmonized protocol exists for resting state fMRI (rsfMRI) data. Here, we propose an initial pipeline for multi-site rsfMRI analysis to allow research groups around the world to analyze scans in a harmonized way, and to perform coordinated statistical tests. The challenge lies in the fact that resting state fMRI measurements collected by researchers over the last decade vary widely, with variable quality and differing spatial or temporal signal-to-noise ratio (tSNR). An effective harmonization must provide optimal measures for all quality data. Here we used rsfMRI data from twenty-two independent studies with approximately fifty corresponding T1-weighted and rsfMRI datasets each, to (A) review and aggregate the state of existing rsfMRI data, (B) demonstrate utility of principal component analysis (PCA)-based denoising and (C) develop a deformable ENIGMA EPI template based on the representative anatomy that incorporates spatial distortion patterns from various protocols and populations.

A bioinformatics workflow for the evaluation of RT-qPCR primer specificity: Application for the assessment of gene expression data reliability in toxicological studies

The reliability of Reverse Transcription quantitative real-time PCR (RT-qPCR) gene expression data depends on proper primer design and RNA quality controls. Despite freely available genomic databases and bioinformatics tools, primer design deficiencies can be found across life science publications. In order to assess the prevalence of such deficiencies in the toxicological literature, 504 primer sets extracted from a random selection of 70 recent rat toxicological studies were evaluated. The specificity of each primer set was systematically analysed using a bioinformatics workflow developed from publicly available resources (NCBI Primer BLAST, in silico PCR in UCSC genome browser, Ensembl DNA database). Potential mismatches (9%), cross-matches (13.5%), co-amplification of multiple gene splice variants (9%) and sub-optimal amplicon sizes (25%) were identified for a significant proportion of the primer sets assessed in silico. Quality controls for gDNA contamination of RNA samples were infrequently reported in the surveyed manuscripts. Hence, the impacts of gDNA contamination on RT-qPCR data were further investigated, revealing that lowly expressed genes presented higher susceptibility to contaminating gDNA. In addition to the retrospective identification of potential primer design issues presented in this study, the described bioinformatics workflow can also be used prospectively to select candidate primer sets for experimental validation.

uap: reproducible and robust HTS data analysis

BACKGROUND

A lack of reproducibility has been repeatedly criticized in computational research. High throughput sequencing (HTS) data analysis is a complex multi-step process. For most of the steps a range of bioinformatic tools is available and for most tools manifold parameters need to be set. Due to this complexity, HTS data analysis is particularly prone to reproducibility and consistency issues. We have defined four criteria that in our opinion ensure a minimal degree of reproducible research for HTS data analysis. A series of workflow management systems is available for assisting complex multi-step data analyses. However, to the best of our knowledge, none of the currently available work flow management systems satisfies all four criteria for reproducible HTS analysis.

RESULTS

Here we present uap, a workflow management system dedicated to robust, consistent, and reproducible HTS data analysis. uap is optimized for the application to omics data, but can be easily extended to other complex analyses. It is available under the GNU GPL v3 license at https://github.com/yigbt/uap.

CONCLUSIONS

uap is a freely available tool that enables researchers to easily adhere to reproducible research principles for HTS data analyses.

Enhanced Probe-Based RT-qPCR Quantification of MicroRNAs Using Poly(A) Tailing and 5' Adaptor Ligation

Probe-based quantitative PCR (qPCR) is a commonly used tool in the realm of real-time qPCR experiments since it is one of the most sensitive detection methods allowing an accurate and reproducible analysis. It uses real-time fluorescence from a fluorescently labeled probe that specifically targets the desired PCR product to measure DNA amplification at each cycle of the PCR. Coupled to a proper reverse transcription step, probe-based qPCR can be efficiently used for the analysis of the expression of difficult targets such as miRNAs. In this chapter, we describe the TaqMan^® advanced miRNA assay in which, owing to a poly(A)-tailing step, the reverse transcription is advantageously performed at once for all the miRNAs in a given sample, and, coupled to the ligation of a 5' universal adapter, allows for a supplementary pre-qPCR amplification step increasing the sensitivity of the assay. Along this protocol, we also provide our general guidelines and advices to perform a reliable and successful quantitative analysis.

Survey on Scientific Shared Resource Rigor and Reproducibility

Shared scientific resources, also known as core facilities, support a significant portion of the research conducted at biomolecular research institutions. The Association of Biomolecular Resource Facilities (ABRF) established the Committee on Core Rigor and Reproducibility (CCoRRe) to further its mission of integrating advanced technologies, education, and communication in the operations of shared scientific resources in support of reproducible research. In order to first assess the needs of the scientific shared resource community, the CCoRRe solicited feedback from ABRF members via a survey. The purpose of the survey was to gain information on how U.S. National Institutes of Health (NIH) initiatives on advancing scientific rigor and reproducibility influenced current services and new technology development. In addition, the survey aimed to identify the challenges and opportunities related to implementation of new reporting requirements and to identify new practices and resources needed to ensure rigorous research. The results revealed a surprising unfamiliarity with the NIH guidelines. Many of the perceived challenges to the effective implementation of best practices (i.e., those designed to ensure rigor and reproducibility) were similarly noted as a challenge to effective provision of support services in a core setting. Further, most cores routinely use best practices and offer services that support rigor and reproducibility. These services include access to well-maintained instrumentation and training on experimental design and data analysis as well as data management. Feedback from this survey will enable the ABRF to build better educational resources and share critical best-practice guidelines. These resources will become important tools to the core community and the researchers they serve to impact rigor and transparency across the range of science and technology.

On resolving ambiguities in microbial community analysis of partial nitritation anammox reactors

PCR-based methods have caused a surge for integration of eco-physiological approaches into research on partial nitritation anammox (PNA). However, a lack of rigorous standards for molecular analyses resulted in widespread data misinterpretation and consequently lack of consensus. Data consistency and accuracy strongly depend on the primer selection and data interpretation. An in-silico evaluation of 16S rRNA gene eubacterial primers used in PNA studies from the last ten years unraveled the difficulty of comparing ecological data from different studies due to a variation in the coverage of these primers. Our 16S amplicon sequencing approach, which includes parallel sequencing of six 16S rRNA hypervariable regions, showed that there is no perfect hypervariable region for PNA microbial communities. Using qPCR analysis, we emphasize the significance of primer choice for quantification and caution with data interpretation. We also provide a framework for PCR based analyses that will improve and assist to objectively interpret and compare such results.

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.

The neuronal migration hypothesis of dyslexia: A critical evaluation 30 years on

The capacity for language is one of the key features underlying the complexity of human cognition and its evolution. However, little is known about the neurobiological mechanisms that mediate normal or impaired linguistic ability. For developmental dyslexia, early postmortem studies conducted in the 1980s linked the disorder to subtle defects in the migration of neurons in the developing neocortex. These early studies were reinforced by human genetic analyses that identified dyslexia susceptibility genes and subsequent evidence of their involvement in neuronal migration. In this review, we examine recent experimental evidence that does not support the link between dyslexia and neuronal migration. We critically evaluate gene function studies conducted in rodent models and draw attention to the lack of robust evidence from histopathological and imaging studies in humans. Our review suggests that the neuronal migration hypothesis of dyslexia should be reconsidered, and the neurobiological basis of dyslexia should be approached with a fresh start.

Launch of an Infrastructure for Health Research: BBMRI-ERIC

Biobanking and BioMolecular resources Research Infrastructure (BBMRI)- European Research Infrastructure Consortium (ERIC) is the largest infrastructure launched in Europe in health research. By nature it is a distributed infrastructure, in which biological samples and data are hosted by the European Member States biobanks. As of today, BBMRI-ERIC consists of 19 European Member States and 1 international organization, the International Agency for Research on Cancer. This means that BBMRI-ERIC has a population of >500 million individuals in Europe. BBMRI-ERIC is a truly Pan-European Research Infrastructure for health research. Given that BBMRI-ERIC is set up to become a key source for users in both academic and scientific institutions as well as in the pharmaceutical and life science industries, it contributes directly to the Innovation Union concept. It is pan-European because BBMRI-ERIC already shows an excellent geographic and regional coverage all over Europe involving countries from South, East, West, North, and Central Europe. BBMRI-ERIC is a service-driven infrastructure for the European Member States, driven by science. The BBMRI-ERIC Directory consists of 100 million samples and a roadmap for better-defined quality in European biobanks for improving reproducibility and reliability of the biological sample and data.

Improving the standardization of mRNA measurement by RT-qPCR

Human health and safety depend on reliable measurements in medical diagnosis and on tests that support the selection and evaluation of therapeutic intervention and newly discovered molecular biomarkers must pass a rigorous evaluation process if they are to be of benefit to patients. Measurement standardization helps to maximize data quality and confidence and ultimately improves the reproducibility of published research. Failure to consider how a given experiment may be standardized can be costly, both financially as well as in time and failure to perform and report pre-clinical research in an appropriately rigorous manner will hinder the development of diagnostic methods. Hence standardization is a crucial step in maintaining the integrity of scientific studies and is a key feature of robust investigation.

Transcriptional-Readthrough RNAs Reflect the Phenomenon of "A Gene Contains Gene(s)" or "Gene(s) within a Gene" in the Human Genome, and Thus Are Not Chimeric RNAs

Tens of thousands of chimeric RNAs, i.e., RNAs with sequences of two genes, have been identified in human cells. Most of them are formed by two neighboring genes on the same chromosome and are considered to be derived via transcriptional readthrough, but a true readthrough event still awaits more evidence and trans-splicing that joins two transcripts together remains as a possible mechanism. We regard those genomic loci that are transcriptionally read through as unannotated genes, because their transcriptional and posttranscriptional regulations are the same as those of already-annotated genes, including fusion genes formed due to genetic alterations. Therefore, readthrough RNAs and fusion-gene-derived RNAs are not chimeras. Only those two-gene RNAs formed at the RNA level, likely via trans-splicing, without corresponding genes as genomic parents, should be regarded as authentic chimeric RNAs. However, since in human cells, procedural and mechanistic details of trans-splicing have never been disclosed, we doubt the existence of trans-splicing. Therefore, there are probably no authentic chimeras in humans, after readthrough and fusion-gene derived RNAs are all put back into the group of ordinary RNAs. Therefore, it should be further determined whether in human cells all two-neighboring-gene RNAs are derived from transcriptional readthrough and whether trans-splicing truly exists.

Knockout Mice for Dyslexia Susceptibility Gene Homologs KIAA0319 and KIAA0319L have Unaffected Neuronal Migration but Display Abnormal Auditory Processing

Developmental dyslexia is a neurodevelopmental disorder that affects reading ability caused by genetic and non-genetic factors. Amongst the susceptibility genes identified to date, KIAA0319 is a prime candidate. RNA-interference experiments in rats suggested its involvement in cortical migration but we could not confirm these findings in Kiaa0319-mutant mice. Given its homologous gene Kiaa0319L (AU040320) has also been proposed to play a role in neuronal migration, we interrogated whether absence of AU040320 alone or together with KIAA0319 affects migration in the developing brain. Analyses of AU040320 and double Kiaa0319;AU040320 knockouts (dKO) revealed no evidence for impaired cortical lamination, neuronal migration, neurogenesis or other anatomical abnormalities. However, dKO mice displayed an auditory deficit in a behavioral gap-in-noise detection task. In addition, recordings of click-evoked auditory brainstem responses revealed suprathreshold deficits in wave III amplitude in AU040320-KO mice, and more general deficits in dKOs. These findings suggest that absence of AU040320 disrupts firing and/or synchrony of activity in the auditory brainstem, while loss of both proteins might affect both peripheral and central auditory function. Overall, these results stand against the proposed role of KIAA0319 and AU040320 in neuronal migration and outline their relationship with deficits in the auditory system.

qPCR primer design revisited

Primers are arguably the single most critical components of any PCR assay, as their properties control the exquisite specificity and sensitivity that make this method uniquely powerful. Consequently, poor design combined with failure to optimise reaction conditions is likely to result in reduced technical precision and false positive or negative detection of amplification targets. Despite the framework provided by the MIQE guidelines and the accessibility of wide-ranging support from peer-reviewed publications, books and online sources as well as commercial companies, the design of many published assays continues to be less than optimal: primers often lack intended specificity, can form dimers, compete with template secondary structures at the primer binding sites or hybridise only within a narrow temperature range. We present an overview of the main steps in the primer design workflow, with data that illustrate some of the unexpected variability that often occurs when theory is translated into practice. We also strongly urge researchers to report as much information about their assays as possible in their publications.

Talking the talk, but not walking the walk: RT-qPCR as a paradigm for the lack of reproducibility in molecular research

Poorly executed and inadequately reported molecular measurement methods are amongst the causes underlying the lack of reproducibility of much biomedical research. Although several high impact factor journals have acknowledged their past failure to scrutinise adequately the technical soundness of manuscripts, there is a perplexing reluctance to implement basic corrective measures. The reverse transcription real-time quantitative PCR (RT-qPCR) is probably the most straightforward measurement technique available for RNA quantification and is widely used in research, diagnostic, forensic and biotechnology applications. Despite the impact of the minimum information for the publication of quantitative PCR experiments (MIQE) guidelines, which aim to improve the robustness and the transparency of reporting of RT-qPCR data, we demonstrate that elementary protocol errors, inappropriate data analysis and inadequate reporting continue to be rife and conclude that the majority of published RT-qPCR data are likely to represent technical noise.

Quality control of digital PCR assays and platforms

Digital polymerase chain reaction (digital PCR, dPCR) is a direct nucleic acid quantification method, thus requiring no standard curves unlike quantitative real-time PCR (qPCR). Nevertheless, evaluation of the linear dynamic range, accuracy, and precision of an assay or platform is recommended, as there are several potential causes of important non-linearity, bias, and imprecision. Ignoring these quality issues may lead to erroneous quantification. This necessitates an approach akin to the construction of standard curves. We study the pitfalls associated with the evaluation of such an experiment, and provide guidelines for the assessment of linearity, accuracy, and precision in dPCR experiments. We present simulation results and a case study supporting the importance of a thorough evaluation. Further, typically presented plots and statistics may not reveal problems with linearity, accuracy, or precision. We find that a robust weighted least-squares approach is highly advisable, yet may also suffer from an inflated false-positive rate. The proposed assessments are also applicable to other analyses, such as the comparison of results obtained from qPCR and dPCR. A web tool for quality evaluation, dPCalibRate, is available.

Toward biotechnology in space: High-throughput instruments for in situ biological research beyond Earth

Space biotechnology is a nascent field aimed at applying tools of modern biology to advance our goals in space exploration. These advances rely on our ability to exploit in situ high throughput techniques for amplification and sequencing DNA, and measuring levels of RNA transcripts, proteins and metabolites in a cell. These techniques, collectively known as "omics" techniques have already revolutionized terrestrial biology. A number of on-going efforts are aimed at developing instruments to carry out "omics" research in space, in particular on board the International Space Station and small satellites. For space applications these instruments require substantial and creative reengineering that includes automation, miniaturization and ensuring that the device is resistant to conditions in space and works independently of the direction of the gravity vector. Different paths taken to meet these requirements for different "omics" instruments are the subjects of this review. The advantages and disadvantages of these instruments and technological solutions and their level of readiness for deployment in space are discussed. Considering that effects of space environments on terrestrial organisms appear to be global, it is argued that high throughput instruments are essential to advance (1) biomedical and physiological studies to control and reduce space-related stressors on living systems, (2) application of biology to life support and in situ resource utilization, (3) planetary protection, and (4) basic research about the limits on life in space. It is also argued that carrying out measurements in situ provides considerable advantages over the traditional space biology paradigm that relies on post-flight data analysis.

Reproducibility of biomedical research - The importance of editorial vigilance

Many journal editors are a failing to implement their own authors' instructions, resulting in the publication of many articles that do not meet basic standards of transparency, employ unsuitable data analysis methods and report overly optimistic conclusions. This problem is particularly acute where quantitative measurements are made and results in the publication of papers that lack scientific rigor and contributes to the concerns with regard to the reproducibility of biomedical research. This hampers research areas such as biomarker identification, as reproducing all but the most striking changes is challenging and translation to patient care rare.

Development of a hydrolysis probe-based real-time assay for the detection of tropical strains of Fusarium oxysporum f. sp. cubense race 4

Fusarium oxysporum f. sp. cubense (Foc) is one of the most important threats to global banana production. Strategies to control the pathogen are lacking, with plant resistance offering the only long-term solution, if sources of resistance are available. Prevention of introduction of Foc into disease-free areas thus remains a key strategy to continue sustainable banana production. In recent years, strains of Foc affecting Cavendish bananas have destroyed plantations in a number of countries in Asia and in the Middle East, and one African country. One vegetative compatibility group (VCG), 01213/16, is considered the major threat to bananas in tropical and subtropical climatic conditions. However, other genetically related VCGs, such as 0121, may potentially jeopardize banana cultures if they were introduced into disease-free areas. To prevent the introduction of these VCGs into disease-free Cavendish banana-growing countries, a real-time PCR test was developed to accurately detect both VCGs. A previously described putative virulence gene was used to develop a specific combination of hydrolysis probe/primers for the detection of tropical Foc race 4 strains. The real-time PCR parameters were optimized by following a statistical approach relying on orthogonal arrays and the Taguchi method in an attempt to enhance sensitivity and ensure high specificity of the assay. This study also assessed critical performance criteria, such as repeatability, reproducibility, robustness, and specificity, with a large including set of 136 F. oxysporum isolates, including 73 Foc pathogenic strains representing 24 VCGs. The validation data demonstrated that the new assay could be used for regulatory testing applications on banana plant material and can contribute to preventing the introduction and spread of Foc strains affecting Cavendish bananas in the tropics.

Mining biomedical images towards valuable information retrieval in biomedical and life sciences

Biomedical images are helpful sources for the scientists and practitioners in drawing significant hypotheses, exemplifying approaches and describing experimental results in published biomedical literature. In last decades, there has been an enormous increase in the amount of heterogeneous biomedical image production and publication, which results in a need for bioimaging platforms for feature extraction and analysis of text and content in biomedical images to take advantage in implementing effective information retrieval systems. In this review, we summarize technologies related to data mining of figures. We describe and compare the potential of different approaches in terms of their developmental aspects, used methodologies, produced results, achieved accuracies and limitations. Our comparative conclusions include current challenges for bioimaging software with selective image mining, embedded text extraction and processing of complex natural language queries.

Toward reliable biomarker signatures in the age of liquid biopsies - how to standardize the small RNA-Seq workflow

Small RNA-Seq has emerged as a powerful tool in transcriptomics, gene expression profiling and biomarker discovery. Sequencing cell-free nucleic acids, particularly microRNA (miRNA), from liquid biopsies additionally provides exciting possibilities for molecular diagnostics, and might help establish disease-specific biomarker signatures. The complexity of the small RNA-Seq workflow, however, bears challenges and biases that researchers need to be aware of in order to generate high-quality data. Rigorous standardization and extensive validation are required to guarantee reliability, reproducibility and comparability of research findings. Hypotheses based on flawed experimental conditions can be inconsistent and even misleading. Comparable to the well-established MIQE guidelines for qPCR experiments, this work aims at establishing guidelines for experimental design and pre-analytical sample processing, standardization of library preparation and sequencing reactions, as well as facilitating data analysis. We highlight bottlenecks in small RNA-Seq experiments, point out the importance of stringent quality control and validation, and provide a primer for differential expression analysis and biomarker discovery. Following our recommendations will encourage better sequencing practice, increase experimental transparency and lead to more reproducible small RNA-Seq results. This will ultimately enhance the validity of biomarker signatures, and allow reliable and robust clinical predictions.

A glance at the applications of Singular Spectrum Analysis in gene expression data

In recent years Singular Spectrum Analysis (SSA) has been used to solve many biomedical issues and is currently accepted as a potential technique in quantitative genetics studies. Presented in this article is a review of recent published genetics studies which have taken advantage of SSA. Since Singular Value Decomposition (SVD) is an important stage of this technique which can also be used as an independent analytical method in gene expression data, we also briefly touch upon some areas of the application of SVD. The review finds that at present, the most prominent area of applying SSA in genetics is filtering and signal extraction, which proves that SSA can be considered as a valuable aid and promising method for genetics analysis.

Design and Sampling Plan Optimization for RT-qPCR Experiments in Plants: A Case Study in Blueberry

The qPCR assay has become a routine technology in plant biotechnology and agricultural research. It is unlikely to be technically improved, but there are still challenges which center around minimizing the variability in results and transparency when reporting technical data in support of the conclusions of a study. There are a number of aspects of the pre- and post-assay workflow that contribute to variability of results. Here, through the study of the introduction of error in qPCR measurements at different stages of the workflow, we describe the most important causes of technical variability in a case study using blueberry. In this study, we found that the stage for which increasing the number of replicates would be the most beneficial depends on the tissue used. For example, we would recommend the use of more RT replicates when working with leaf tissue, while the use of more sampling (RNA extraction) replicates would be recommended when working with stems or fruits to obtain the most optimal results. The use of more qPCR replicates provides the least benefit as it is the most reproducible step. By knowing the distribution of error over an entire experiment and the costs at each step, we have developed a script to identify the optimal sampling plan within the limits of a given budget. These findings should help plant scientists improve the design of qPCR experiments and refine their laboratory practices in order to conduct qPCR assays in a more reliable-manner to produce more consistent and reproducible data.

Improving the reliability of peer-reviewed publications: We are all in it together

The current, and welcome, focus on standardization of techniques and transparency of reporting in the biomedical, peer-reviewed literature is commendable. However, that focus has been intermittent as well as lacklustre and so failed to tackle the alarming lack of reliability and reproducibly of biomedical research. Authors have access to numerous recommendations, ranging from simple standards dealing with technical issues to those regulating clinical trials, suggesting that improved reporting guidelines are not the solution. The elemental solution is for editors to require meticulous implementation of their journals' instructions for authors and reviewers and stipulate that no paper is published without a transparent, complete and accurate materials and methods section.

A Panel of Stably Expressed Reference Genes for Real-Time qPCR Gene Expression Studies of Mallards (Anas platyrhynchos)

Determining which reference genes have the highest stability, and are therefore appropriate for normalising data, is a crucial step in the design of real-time quantitative PCR (qPCR) gene expression studies. This is particularly warranted in non-model and ecologically important species for which appropriate reference genes are lacking, such as the mallard--a key reservoir of many diseases with relevance for human and livestock health. Previous studies assessing gene expression changes as a consequence of infection in mallards have nearly universally used β-actin and/or GAPDH as reference genes without confirming their suitability as normalisers. The use of reference genes at random, without regard for stability of expression across treatment groups, can result in erroneous interpretation of data. Here, eleven putative reference genes for use in gene expression studies of the mallard were evaluated, across six different tissues, using a low pathogenic avian influenza A virus infection model. Tissue type influenced the selection of reference genes, whereby different genes were stable in blood, spleen, lung, gastrointestinal tract and colon. β-actin and GAPDH generally displayed low stability and are therefore inappropriate reference genes in many cases. The use of different algorithms (GeNorm and NormFinder) affected stability rankings, but for both algorithms it was possible to find a combination of two stable reference genes with which to normalise qPCR data in mallards. These results highlight the importance of validating the choice of normalising reference genes before conducting gene expression studies in ducks. The fact that nearly all previous studies of the influence of pathogen infection on mallard gene expression have used a single, non-validated reference gene is problematic. The toolkit of putative reference genes provided here offers a solid foundation for future studies of gene expression in mallards and other waterfowl.

Guiding our PCR experiments

The MIQE guidelines for qPCR and dPCR have been around for a while now, but few are taking advantage of this resource. Jeffrey Perkel looks at challenge of standardizing PCR.