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Top 5 reasons your qPCR data was rejected: An insider perspective

By: Roche Life Science

Posted: October 26, 2015 | Lab Life : Real-Time PCR

You finally finished all the replicate experiments, analyzed and reanalyzed the data, wrote and revised the manuscript, and completed the dreaded online submission steps. And you wait. And wait. Then, after weeks of anxiously (or compulsively) checking your email for communication from the editorial office, you finally receive official word that your paper was rejected. After a few tears, interspersed by stuttered whimpers, and a few textbooks thrown against the wall, you pull yourself together and plan your next move. After all, what kind of scientist would you be without facing adversity in the all-too-familiar form of rejection?

Unfortunately, this is not an uncommon phenomenon in the realm of basic science manuscripts, and in particular, with qPCR-based studies. However, there are strategies to improve your chances of success and maximizing presentation of your qPCR data. Therefore, in this article, we will discuss the top five reasons your qPCR data was rejected and how to combat these pitfalls:

1. Insufficient quantitation: The era of semi-quantitative or even qualitative gene expression studies is long over. The widespread ease and availability of qPCR-based assays has made the criteria for robust analysis a baseline expectation. Your qPCR studies should be sufficiently replicated and statistically analyzed. The data should be reported in a clear and concise manner. The reader should know how many independent experiments were performed, the precise conditions of the samples, and the type of statistical analysis conducted. If performing larger-scale analyses that require more complex statistical analysis, the use of a biostatistician is key, as reviewers often look for this now. Indeed, many journals now include a biostatistician in their review processes, so getting ahead of the game with this will only benefit you in the long run.

2. Incomplete methods: This can come from multiple areas, including not enough information to understand the methodology or replicate the experiment. The reader needs to be able to know exactly how the cells or tissue samples were treated and collected, how the DNA or RNA was extracted, and how the qPCR analysis was performed. This is true for all experiments in your paper, and it brings us to point No. 3 below.

3. Lack of MIQE compliance: The minimum information for publication of quantitative real-time PCR experiments (MIQE) guidelines were first reported by Bustin et al. in 2009 in Clinical Chemistry1. The goal of the MIQE was to establish a consensus on how to improve reporting of qPCR experimental data to enhance reliability of results in the scientific literature and to promote inter-laboratory consistency and experimental transparency. The MIQE guidelines include full disclosure of all reagents, target information, primer and probe sequences, and all methodological analysis required for reproducibility. In addition to proper nomenclature use, including when to use terms such as qPCR versus RT-qPCR, hydrolysis, or dual hybridization probes, MIQE guidelines include requirements for description of nucleic acid extraction, target information, primer and probe information, qPCR reaction and validation steps, as well as data analysis information. If your paper lacks these essential pieces of information, reviewers are sure to request its inclusion or clarification. Therefore, providing this information upfront, even abbreviated as supplemental methods, can save you this critique from your reviewers.

4. Scientific writing: The importance of good scientific writing cannot be understated. Sometimes, rejection of data by reviewers has less to do with the data itself and more to do with the ability to communicate that data effectively. Therefore, soundly introducing the relevance of your performed studies with clear and concise descriptions of your data can make the difference between good data and a great paper. Try to have a colleague or two review and critique your manuscript prior to submission or even utilize a scientific editor if your institution has this resource available. Be sure your figures and legends provide all necessary information without having to refer to additional materials and that your figures themselves are of optimal resolution for reading labels and graphics. The more you review manuscripts with unfamiliar data, the more you will appreciate when figures have clarity and ease of interpretation.

5. Biological relevance: Lastly, even when you have effectively communicated the methodology and rationale of your qPCR data, sometimes the biologic relevance can remain unclear to the reader. As the author, it is your job to help the reviewers and readers understand the importance of your work and how it impacts and advances the field. Perhaps the reviewers will be experts in a related field with the intelligence to understand and critique your data, but a lack of intricate knowledge in your field niche to understand the meaning of your findings and how they fill a fundamental gap in critical knowledge could be detrimental. The onus is therefore on you to convey this message with your writing and data. Conversely, the reviewers will often feel obligated to make experimental suggestions to strengthen this argument, as they are charged with responsibility to assess the novelty and impact of your data.

1. Bustin SA et al., The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments, Clinical Chemistry. 2009; 55(4): 611-22

 

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