High output Next Generation Sequencing (NGS) technologies have become more accessible to researchers and scientists interested in unraveling the intricacies and depth surrounding genomic research. Compared to decades ago, the monetary cost has significantly reduced, alongside more high yield, error-free results. However, to achieve the desirable results, a number of steps must be completed in a methodical fashion. These will ensure the accuracy of your results plus higher sequencing productivity.
Genome sequencing services are currently utilized for a myriad of purposes: human disease research, cataloging entire disease genes, sequencing the genome of entire species, cataloging and much more. However, most, if not all, NGS technologies follow a very similar workflow. Although techniques may vary, the actual sequencing stage remains fundamentally the same, thus, therein lies the importance of maximizing your workflow’s quality and research output, since the little details may alter the results.
Selecting optimal and carefully handled pieces of tissue for your genomic sequencing is incredibly important. The type of tissue determines the amount of DNA or RNA extracted, the storage selection (Formalin-Fixed Paraffin-Embedded, FFPE vs fresh tissue), its shipping and the purification process.
Ensure the quality of your starting material. If the starting material used for the library is inefficient or poor, your results will be likewise poor. Contamination is often a cause of poor-quality starting material. Contaminants may come from:
Another important factor to consider is the DNA sample size. Albeit current NGS platforms are capable of amplifying and sequencing small amounts of input DNA, it is always recommendable to use the minimum input DNA specified by the manufacturer (typically from 200 to 20000 nanograms of DNA). The logic is that, the less amount of samples you use, the higher risk you are at encountering bias.
Mindful laboratory practices are important, too, during the library preparation. Temperature and reaction time are very important conditions capable of modifying the enzymatic protocol, especially during the processes of ligation and tagmentation. The tagmentation is to “tags” the fragmented the DNA samples with fluorescent signals to determine the nucleotides sequence[2, 3].
Avoid cross-contamination by being mindful enough to change gloves frequently, changing tips between pipetting steps and avoiding the pipette shaft touches in the inside of the tubes during the multiplexing processes. A single contaminated sample will ruin the entirety of your work and its results. Keep your surface area as clean as possible, utilize RNase-free microfuge tubes and be careful of volume errors while pipetting.
Novogene is one of the most reputable NGS companies on a global scale. Their strong scientific expertise, their reliability and technological capacity place them at the vanguard of the NGS sequencing partnership, with rich experience in improving your results. Proof of this is the significant number of research papers published in highly reputable journals, such as Cell, Nature and Science.
Including biological replications in your study is very important in your NGS services if you are studying genetic variants linked to a health condition[4]. This is done by inducing mutations (polymorphisms) in the genome through different methods (UV light, X-rays, fast neutrons or chemical mutagens), to establish evidence of gene function and their possible role in the pathogenesis of diseases[5].
Lack of sufficient replication elevates the inherent error rate of genomic services, thus, generating false-positives. NGS provides cost effective, high-throughput solutions. Researchers hereby are able to replicate experiments, detecting the presence of any false positive variants during the mutation inducing research.
Leaps in technology development by genome sequencing companies have significantly diminished the error rate in NGS, but that doesn’t mean they have been completely eradicated[6]. Each sequencing platform provides distinctive advantages and disadvantages, picking the best-suited NGS genomics platform for the type of research you want to conduct will minimize any unwanted miscalls.
Novogene offers their customers with excellent, reliable and capable platforms. The advanced platforms, such as Illumina NovaSeq and Hiseq systems, Pacbio sequel and Nanopore PromethION, are examples of the high level NGS technology that Novogene can provide, characterized by unprecedented engineering, long sequencing reading, incredible output and cost effectiveness.
Finally, when performing data analysis, remain skeptical. Reproducing your results over and over again will help you discern if your findings were accurate or the result of a poor-quality workflow. Consulting the knowledgeable expertise that characterizes Novogene’s scientific vanguard is very important as well, they can help you answer any doubts or identify possible mistakes in your research.
All in all, asserting quality control is pivotal to ensure your end results are contamination free, to minimize the risk of bias as much as possible and check for the inherent and systematic errors present in the sequencing platforms. Otherwise, the possibilities of a false positive, mismatch during the sequencing process and much more puts your entire work at hazard.
[1] Natasha Beeton-Kempen, Ph.D. 8 Tips for Improving Your NGS Libraries. [Technology Networks] [2] David M. Pereira, João C. Fernandes, Patrícia Valentão, Paula B. Andrade, Chapter 2.1.2 – “Omics” Technologies: Promises and Benefits for Molecular Medicine, Editor(s): Martin Wehling, Principles of Translational Science in Medicine (Second Edition), Academic Press, 2015, Pages 25-39. [ScienceDirect] [3] Whole Genome Sequencing and Re-sequencing Guide. [GenoHub] [4] Liu DJ, Leal SM. Replication strategies for rare variant complex trait association studies via next-generation sequencing. Am J Hum Genet. 2010;87(6):790-801. [Am J Hum Genet.] [5] Addo-Quaye C, Tuinstra M, Carraro N, Weil C, Dilkes BP. Whole Genome Sequence Accuracy Is Improved by Replication in a Population of Mutagenized Sorghum. G3 (Bethesda). 2018;8(3):1079-1094. Published 2018 Mar 2. [G3 Bethesda] [6] Bravo, H.C. and Irizarry, R.A. (2010), Model‐Based Quality Assessment and Base‐Calling for Second‐Generation Sequencing Data. Biometrics, 66: 665-674. [Biometrics]
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