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An introduction to efficient planning and execution of RNA sequencing (RNA-Seq) experiments. RNA sequencing (RNA-Seq) refers to a method that is based on next genera - tion sequencing (NGS) technologies to study transcriptomes. While microar - ray-based technologies depend on measuring hybridization intensities to predesigned probes, RNA-Seq relies on discrete counting of sequenced mol - ecules. Thus, in contrast to microar - rays, RNA-Seq requires no prior knowl - edge about the genome and can be considered hypothesis free. In addi - tion, the counting of RNA molecules gives RNA-Seq experiments a much higher dynamic range compared to the hybridization intensities mea - sured in microarray experiments. Also considering the falling costs of NGS technologies, it is not surprising that RNA-Seq experiments have become the gold standard in transcriptome studies. Novel isoforms, alterna - tive splice sites, rare transcripts and gene-fusions, non-coding transcripts, and additional, even novel mecha - nism, can be detected all in a single experiment. Usually, the main goal of RNA-Seq studies is to obtain expres - sion profiles, pathways and gene net - works linked to the experimental con - dition studied. A generalized work?ow of a typical RNA-Seq study is depicted in Figure 1 . Given the complex orga - nization of genomes together with the huge amount of fragmented data, the interpretation of RNA-Seq experiments may appear a daunting task, especially for eukaryotic organ - isms . For instance, the most recent human reference assembly – GRCh38 – has 244’550 unique exons with a mean length of 330 bases and a total amount of 80 million bases scattered across the 3 billion bases of the human genome. There are 2’879 annotated non-coding micro RNA (miRNA) , 52’000 transcripts from 26’475 genes, 22’302 associated gene ontology (GO) terms  and 330 KEGG pathways  (as of August 2018). Thus, a good experimental strategy is important to reliably identify the desired genes and gene networks, for example the tran - scription targets of a stressor, or a spe - cific gene or pathway of interest after treatment, or gene-expression differ - ences between different genotypes. This white paper will give an overview on how to handle RNA-Seq data by presenting a selection of workflows. RNA Sequencing Figure 1. This figure depicts a generalized RNA sequencing workflow that may be used for differential expres - sion analysis. Motivation for RNA Sequencing Data AnalysisSamples Total RNA Isolation RNA Library Preparation Illumina Short Read Sequencing Report Generation Experimental Design Microsynth AG, SwitzerlandSch?tzenstrasse 15 ? P.O. Box ? CH - 9436 Balgach ? Phone + 41fi71fi722fi83 33 ? Fax + 41fi71fi722fi87 58 ? info @microsynth.ch ? www.microsynth.ch THE SWISS DNA COMPANY White Paper ? Next Generation Sequencing RNA Isolation Obtaining high quality RNA is critical. RNA degradation is detrimental to the experiments since it may introduce 3’ biases during polyadenylation (polyA) enrichment or may distort the tran - script profile by differentially affect - ing different RNAs. Thus, great care is needed to preserve the integrity of the input RNA. The acronym GIGO “garbage in, garbage out” holds true in this case as well. A notable excep - tion is RNA extracted from formalde - hyde-fixed paraffin-embedded (FFPE) tissue obtained by laser-assisted dis - section methods, where a certain amount of degradation is unavoid - able. Transcript profiles may also be distorted upon amplification of low amounts of input RNA, using either transcription-based or PCR-based amplification methods. However, with careful controls and a sufficient number of biological replicates, the adverse effects can be minimized. Sequencing Library Construction Depending on the desired RNA type (coding or non-coding) and type of organism studied (eukaryote or pro - karyote), different sequencing library types are constructed. For instance, to sequence mRNA, a polyA enrich - ment step is performed for eukary - otes, while a ribosomal RNA deple - tion step is carried out for prokaryotes. Kits for non-coding RNA library con - struction may use alternative tech - niques to enrich the relevant RNA fraction. The constructed libraries are stranded, meaning they retain the strand information of the sequenced molecule, which results in a more reli - able quantification of gene expression . One typical method to keep the RNA strandness makes use of uracil instead of thymine for incorporation during second strand cDNA synthesis. After adapter ligation and before PCR amplification, uracil-DNA glycosylase (UNG) is added to degrade the second strand. As a result, all reads start in the same orientation, allowing the iden - tification of the transcribed strand. A schematic depiction of how total RNA is turned into a sequenceable Illumina cDNA library is shown in Figure 2 . Experimental Design For a successful experiment, many aspects, including experimental setup, sampling, and funding are to be con - sidered. In addition, the number of biological replicates and the number of reads produced for each replicate are essential parameters to produce valid results , especially to detect the maximal number of diff erentially expressed genes which includes rare transcripts. As gene expression anal - ysis builds on counting reads from the respective transcription unit, sin - gle-end reads of 75 bases length usually suffice for accurate mapping. However, paired-end sequencing (and in some cases longer reads, for instance as produced by Pacific Biosciences (PacBio) sequencing technologies) is required if highly accurate transcript quantification, determination of gene fusions or novel splice variant detec - tion is envisaged. In contrast to sin - gle-end sequencing, paired-end sequencing enables reading both ends of a (c)DNA fragment. Generally, it is recommended to work at least in trip - licates per experimental condition and sequence 30 million single-end reads per replicate for eukaryotic organisms and 10 million single-end reads for each replicate for prokaryotic organ - isms. For miRNA the read numbers may be halved. It is also worth men - tioning that the External RNA Controls Consortium (ERCC) has developed a set of external RNA controls designed to mimic natural eukaryotic mRNA sequences . These sequences may be spiked in after RNA isolation and can be used to estimate the uncertainty in the subsequent measurements. Sequencing and Differential Expression Analysis of Coding and Non-coding RNA Selected Applications of RNA-Seq Transcriptome studies are well suited to understand disease mech - anisms, developmental mecha - nisms, or response to various stress - ors. Differential expression analysis of RNA-Seq data relies on the compari - son of data sets obtained from exper - imental conditions (e.g. drug treat - ments) and controls to determine the difference in transcript abun - dance. The focus here is on messen - ger RNA (mRNA). In addition, non- coding miRNAs, which often have gene regulatory purposes, may be used to develop biomarkers specific to a medical condition. Such differ - entially expressed miRNA, can then be experimentally verified to develop diagnostic qPCR kits for instance. Microsynth AG, SwitzerlandSch?tzenstrasse 15 ? P.O. Box ? CH - 9436 Balgach ? Phone + 41fi71fi722fi83 33 ? Fax + 41fi71fi722fi87 58 ? info @microsynth.ch ? www.microsynth.ch THE SWISS DNA COMPANY White Paper ? Next Generation Sequencing Bioinformatics Analysis As an example, let us consider an RNA-Seq experiment aimed at detect - ing changes in the gene expression profile of a human cell line after expo - sure to a drug. With control samples and additional samples taken at two different time points after drug appli - cation, each in three replicates, the total sample number would amount to nine. It is strictly recommended to not pool different replicates or condi - tions into a single sample for sequenc - ing as this would eliminate all statisti - cal power and the experiment would become useless. Assuming each sample in the outlined RNA-Seq exper - iment generates 30 million single-end, 75 bases long reads, the whole exper - iment produces 270 million reads or 20 billion bases. This large amount of data requires a dedicated analysis pipeline to extract meaningful infor - mation. Bioinformatics analysis of RNA-Seq data generally consists in: 1) quality control, optional size selection (e.g. to specifically separate non-cod - ing RNA fractions) and filtering of the sequenced reads, 2) splice-aware mapping of the reads to the refer - ence genome, 3) counting of uniquely mapped reads for each gene, 4) normal - ization of read counts across the exper - iment and 5) statistical evaluation of the normalized values comparing the different conditions (such as treatment and control) to each other to iden - tify significant fold changes and up- or down-regulation of the genes . Table 1 presents an excerpt of a mRNA differential gene expression analy - sis. Figure 4 shows how expression values of replicates group differ from the values of the respective controls. Next Generation Sequencing Illumina short-read sequencing by syn - thesis (SBS) technology, as depicted in Figure 3 , is especially well suited for RNA-Seq, as it is fast, accurate and cost effective . Sequenced reads are pro - duced in the standard fastq format  that incorporates both sequence infor - mation and quality scoring and can be further processed in downstream anal - yses. Figure 4. Principal Component Analysis (PCA) plot to visualize grouping of samples in an RNA-Seq experiment. The three conditions depicted are clearly separated, indicating significant, differential gene expression patterns of the three analyzed con - ditions. Flow Cell 5‘3‘ Flow Cell 5‘3‘ Flow Cell 5‘3‘ Flow Cell 5‘3‘ First strand sequencing Indexing Flipping and second strand sequencing Index read Sequence read 2 will be sense Sequence read 1 will be antisense Sense DNA Sense DNA Sense DNA Anti-sense DNA Figure 3: Schematic of Illuminas paired-end sequencing workflow. Figure 2. Schematic description of a poly-A enriched RNA Illumina library ready for sequencing. Image: David Corney. Microsynth AG, SwitzerlandSch?tzenstrasse 15 ? P.O. Box ? CH - 9436 Balgach ? Phone + 41fi71fi722fi83 33 ? Fax + 41fi71fi722fi87 58 ? info @microsynth.ch ? www.microsynth.ch THE SWISS DNA COMPANY White Paper ? Next Generation Sequencing Figure 6. A depiction of a significant de novo miRNA motif discovered in a miRNA Seq analysis. A miRNA motif is a region that is well conserved in many of the analyzed sequences. Figure 5. Excerpt from the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway graph “TRANSCRIPTIONAL MISREGULATION IN CANCER”, where colored nodes represent significantly up- or downregulated genes in the selected pathway. Based on the differential gene expres - sion results and depending on the content of gene information published in databases, gene set and pathway analysis may be carried out to illumi - nate the larger context of the involved metabolic processes as exemplified in Figure 5 . A useful additional anal - ysis in the case of miRNAs comprises a motif search to identify potential miRNA targets and to uncover addi - tional, novel miRNAs . The results of such analyses may be submitted to public databases such as miRNet  for further network-based visual analy - sis. Figure 6 depicts such a motif iden - tified by a miRNA analysis. Table 1. This excerpt of a table shows the main output of a differential gene expression analysis. In this experiment two conditions with three replicates are compared to each other. The table lists from left to right the gene identifier, boxplots represent - ing expression level distributions of the replicates, the log 2 fold change of gene expression between condition 1 and condition 2, the propability value (p-value) of the log 2 fold change and the p-value adjusted for multiple testing. Repression of tumor supressors Inhibition of apoptosis Cell survival Apoptosis Inhibition of apoptosis Proliferation? < Neuroendocrine cancers> Neuroblastoma Amplifcation Carcinoid Mutation MYCN MEN1 MLL MAX SP1ZBTB17(TF) (TF) TF DNA DNA DNA MDM2 PTK2 TP53 COMMD3-BMI1 NTRK1 NGFR CDKN1B 2.4 0 2.3 fold change Microsynth AG, SwitzerlandSch?tzenstrasse 15 ? P.O. Box ? CH - 9436 Balgach ? Phone + 41fi71fi722fi83 33 ? Fax + 41fi71fi722fi87 58 ? info @microsynth.ch ? www.microsynth.ch THE SWISS DNA COMPANY White Paper ? Next Generation Sequencing Diferential gene expression in eukaryotes Analysis Method Experimental Setup Material and Resources Sample Preparation Sequencing Data Analysis Diferential gene expression in prokaryotes Non-coding RNA diferential expression analysis in eukaryotes Alternative splice-sites and gene-fusion detection (novel isoforms) De novo transcriptome assembly At least two conditions in replicates, no pooling of diferent conditions Pooling of diferent tissues, growth stadiums, etc. to capture the transcriptome in its entirety mRNA and availability of annotated reference genome mRNA and availability of annotated reference genome e.g. miRNA and availability of annotated non-coding RNA and reference genome mRNA and availability of annotated reference Genome mRNA, missing annotated reference Genome Total RNA isolation; stranded polyA enriched sequencing library Total RNA isolation; stranded ribo-depleted sequencing library Total RNA isolation; non-coding RNA enriched sequencing library Total RNA isolation; stranded polyA enriched sequencing library Total RNA isolation; normalized mRNA sequencing library 30 Mio single-end reads, 75 bp length 10 Mio single-end reads, 75 bp length 15 Mio single-end reads, 75 bp length 50 Mio paired-end reads, 2 x 150 bp length 20 Mio paired-end reads, 2 x 300 bp length Diferential gene expression analysis; pathway analysis if pathway database for the organism in question is available De novo transcriptome assembly and annotation Common Scientifc Question Study the transcriptome of a yet uncharted species Study cancer specifc mechanisms Develop biomarkers for specifc medical conditions Explore the infuence of a treatment on prokaryotic gene expression Explore the infuence of a treatment on eukaryotic gene expression At least two conditions in replicates, no pooling of diferent conditions At least two conditions in replicates, no pooling of diferent conditions Diferential gene expression analysis; pathway analysis if pathway database for the organism in question is available Diferential expression analysis; motif search Statistical appraisal of detected alternative splice sites and gene fusions At least two conditions in replicates, no pooling of diferent conditions Table 2. This table provides an overview of common scientifc questions in the field of RNA-Seq and gives a brief overview of the most important points that need to be considered in a RNA-Seq project. The table is intended as a quick reference guide. Summary Obviously, RNA-Seq is not limited to dealing with questions of differen - tial gene expression or identification of miRNA, which have been discussed in the previous sections. Table 2 lists common RNA-Seq applications. The table can serve as a guide for selecting an appropriate approach to a research question. Another application of RNA Seq technology is, for example, de novo transcriptome assembly and annota - tion, which is useful when no anno - tated reference genome is available. In short, RNA is collected from as many different stages and tissues as possi - ble. The entire RNA is then enriched for polyadenylated mRNA. The pool of mRNA, which ideally represents all transcribed genes, is then normal - ized to reduce abundant mRNAs and enrich rare mRNAs. The normalized transcripts are sequenced, then assem - bled in a second step and annotated with various databases in a third step, resulting in a ready-to-use de novo transcriptome . RNA-Seq provides a snapshot of the transcriptome in cells and cell pop - ulations, making it a very attractive and powerful method. However, the results of the RNA-Seq experiments are complex because they produce a large amount of fragmented data. However, with the right approach, the challenge of extracting knowledge is reduced to a manageable task. Microsynth AG, SwitzerlandSchützenstrasse 15 · P.O. Box · CH - 9436 Balgach · Phone + 41f71f722f83 33 · Fax + 41f71f722f87 58 · info @microsynth.ch · www.microsynth.ch THE SWISS DNA COMPANY White Paper · Next Generation Sequencing References  Steven L. Salzberg. Open ques - tions: How many genes do we have? BMC Biology. 2018;16(94). doi:10.1186/ s12915-018-0564-x  Sam Griffiths-Jones, Russell J. Grocock, Stijn van Dongen, Alex Bateman, Anton J. Enright; miRBase: microRNA sequences, targets and gene nomenclature, Nucleic Acids Research, Volume 34, Issue suppl_1, 1 January 2006, Pages D140–D144, https://doi. org/10.1093/nar/gkj112  The Gene Ontology Consortium; Expansion of the Gene Ontology knowl - edgebase and resources, Nucleic Acids Research, Volume 45, Issue D1, 4 January 2017, Pages D331–D338, https://doi. org/10.1093/nar/gkw1108  Minoru Kanehisa, Miho Furumichi, Mao Tanabe, Yoko Sato, Kanae Morishima; KEGG: new perspectives on genomes, pathways, diseases and drugs, Nucleic Acids Research, Volume 45, Issue D1, 4 January 2017, Pages D353–D361, https://doi.org/10.1093/nar/gkw1092  Schurch NJ, Schofield P, Gierli?ski M, et al. How many biological replicates are needed in an RNA-seq experiment and which differential expression tool should you use? RNA. 2016;22(6):839- 851. doi:10.1261/rna.053959.115  Lemire A, Lea K, Batten D, et al. Development of ERCC RNA Spike-In Control Mixes. Journal of Biomolecular Techniques : JBT. 2011;22(Suppl):S46  Zhao S, Zhang Y, Gordon W, et al. Comparison of stranded and non- stranded RNA-seq transcriptome profil - ing and investigation of gene overlap. BMC Genomics. 2015;16(1):675. doi:10.1186/s12864-015-1876-7  Online at: https://emea.illumina. com/systems/sequencing-platforms/ nextseq/applications.html?langsel=/ ch/, accessed 14.09.2018  Online at: http://maq.sourceforge. net/fastq.shtml, accessed 14.09.2018  Sandrine Borgeaud, Lisa C. Metzger, Tiziana Scrignari, Melanie Blokesch, The type VI secretion system of Vibrio chol - erae fosters horizontal gene transfer, Science 02 Jan 2015: Vol. 347, Issue 6217, pp. 63-67. DOI: 10.1126/science.1260064  Bhupesh K. Prusty, Nitish Gulve, Suvagata Roy Chowdhury, Michael Schuster, Sebastian Strempel, Vincent Descamps, Thomas Rudel. HHV-6 encoded small non-coding RNAs define an intermediate and early stage in viral reactivation. npj Genomic Medicine. 2018;3(25). 10.1038/s41525-018-0064-5  Yannan Fan, Keith Siklenka, Simran K. Arora, Paula Ribeiro, Sarah Kimmins, Jianguo Xia; miRNet - dissecting miR - NA-target interactions and functional associations through network-based visual analysis, Nucleic Acids Research, Volume 44, Issue W1, 8 July 2016, Pages W135–W141, https://doi.org/10.1093/ nar/gkw288  Neves, R.C., Guimaraes, J.C., Strempel, S. et al., Transcriptome pro - filing of Symbion pandora (phylum Cycliophora): insights from a differential gene expression analysis, Org Divers Evol (2017) 17: 111. https://doi.org/10.1007/ s13127-016-0315-1 Microsynth AG, SwitzerlandSch?tzenstrasse 15 ? P.O. Box ? CH - 9436 Balgach ? Phone + 417172283 33 ? Fax + 417172287 58 ? info @microsynth.ch ? www.microsynth.ch THE SWISS DNA COMPANY White Paper ? Next Generation Sequencing
Contract research capabilities in the field of molecular genetics delivered how, where and when you need it. Microsynth has been founded more than 30 years ago as a DNA and RNA oligo synthesis service company. Step by step, additional services such as Sanger sequencing, polymerase chain reaction (PCR), real-time PCR (qPCR) and digital PCR services, and Next- Generation Sequencing (NGS) were added. By now, a comprehensive toolbox covering the realm of molec - ular genetics is at Microsynth’s dispo - sition. Microsynth’s skills in combining the different methods to establish a tai - lored workflow to successfully meet the customer’s demand has constantly grown with each project and challenge mastered. Here, we want to provide an overview how Microsynth can suit customers with different needs in con - tract research capabilities, including clients who need to comply with reg - ulatory demands. In a general view, the relevant core parameters in molecular genetics are the sequences of DNA and RNA mol - ecules, as well as by the abundance of DNA and RNA molecules with a given sequence identity. Or, in other words, the main analytical tasks are (1) to decipher or to produce the correct DNA and RNA sequences, and (2) to count or quantify DNA and RNA mol - ecules with a given sequence. In addi - tion (3), data interpretation consists of comparing sequences and their abun - dances to references and/or among different samples. In the light of this, the main methods of our portfolio are shortly discussed, with advantages and limitations. Custom Contract Research Services Introduction Scientific Methods Expertise Sanger sequencing is useful to deci - pher the DNA sequence of molecules up to 1’000 nucleotides per reaction. A DNA primer and sufficient tem - plate DNA are required for its success. Therefore, for each reaction, some sequence information must be known, and it cannot be directly applied on genomic DNA without a preceding PCR amplification. Sanger sequenc - ing is relatively fast and cheap, and it is mostly limited to homogenous samples. Next Generation Sequencing (NGS), typically performed on the Illumina sequencing platforms (see Figure 1 ), in turn provides massive parallel sequencing of millions, even billions of molecules. This allows the determina - tion of up to 2’400 Gb in one sequenc - ing run. In principle, no prior sequence information is required, however, the focus on defined sequences via ampli - con sequencing represent a wide - spread application. NGS has revo - lutionized molecular genetics and opened a wealth of new applications. However, the read length of Illumina sequencing reaction is limited to 300 nucleotides paired-ended. This means that long DNA molecules, for example genomes, are fragmented into multi - ple small pieces for sequencing. The sequence information of the long original fragments needs to be recon - structed with computational methods, which are limited, especially due to the presence of repetitive sequence. More recently, long-read sequencing technologies such as Oxford Nanopore or PacBio have been developed to overcome these limitations and are increasingly popular to complement or even substitute Illumina short-read sequencing. The disadvantage of short Illumina reads does not apply to short templates such as cDNA derived from transcribed RNA, or PCR amplicons of up to about 500 base pairs (bp). In addition to identifying DNA and RNA sequences, NGS can also be used to count molecules. For example, Microsynth AG, SwitzerlandSch?tzenstrasse 15 ? P.O. Box ? CH - 9436 Balgach ? Phone + 41ff71ff722ff83 33 ? Fax + 41ff71ff722ff87 58 ? info @microsynth.ch ? www.microsynth.com THE SWISS DNA COMPANY White Paper ? Next Generation Sequencing using RNA sequencing the abun - dance of a given mRNA is determined by assessing the number of normal - ized reads. Similarly, the abundance of a given microbial species is deter - mined by the relative number of matching sequences using an ampli - con metagenomics approach. A similar logic applies to the fraction of success - ful edits in a CRISPR/Cas9 experiment. To precisely determine the number of specific RNA or DNA molecules at rela - tively lower cost and in higher sample throughput settings compared to NGS, PCR methods are recommended, spe - cifically quantitated real-time PCR (qPCR) or digital PCR. With qPCR, the amount of amplified DNA is measured upon each PCR cycle, taking advantage of the activation of fluorescence upon product formation. The number of PCR cycles required to reach a certain signal threshold correlates with the amount of starting template. However, the actual efficiency of each amplification cycle must be considered to correctly infer the amount of starting material. In contrast, digital PCR is almost insen - sitive to reaction efficiency, as long as the reaction produces a signal discern - able from background. Unlike qPCR, dPCR reactions are compartmental - ized into 20’000 distinct sub-reactions (droplets), each of which contains a single template molecule on average. The outcome of each sub-reaction is then qualified as either positive or negative. The number of positive reac - tions directly relates to the number of template present in the reaction. Thus, dPCR allows direct counting of tem - plate molecules and is less suscepti - ble to PCR inhibition effects from the matrix. These advantages translate to increased robustness and precision of dPCR compared to qPCR. On the other hand, dPCR is more costly; thus, qPCR will remain useful where precision and robustness is not of prior importance. For example, Figure 1. Operator using Illumina MiSeq Sequencer. Figure 2. Operator loading the liquid handler for DNA / RNA isolation. Microsynth AG, SwitzerlandSch?tzenstrasse 15 ? P.O. Box ? CH - 9436 Balgach ? Phone + 41fi71fi722fi83 33 ? Fax + 41fi71fi722fi87 58 ? info @microsynth.ch ? www.microsynth.com THE SWISS DNA COMPANY White Paper ? Next Generation Sequencing Bringing it All Together To address the specific customer needs, different methods are combined in customized analysis workflows. All experimental results are critically eval - uated to determine how reliably they describe and represent the actual samples. Thereby can Microynth con - tribute to the safety of drug products for the consumer and patients, and to fulfill regulatory documentation and experimental guidelines requested by US and European authorities. An important resource is issued by the The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) (https://www.ich.org/). At Microsynth, we identify the relevant experimental parameters and assays to be addressed based on ICH guidelines. For example, when setting-up a method, Microsynth will evaluate its robustness. This allows identifying how parameters such as temperature, reagent concentrations, DNA or RNA isolation procedures, etc. affect the results. Precision refers to how variable the results are when a given assay is repeated on different days with different operators, reagent lots, or even in different laboratories (intermediate precision). Accuracy describes how close the determined results is to the true result, which refers to the value obtained with an alterna - tive method that could be considered the gold standard. Different questions are addressed for distinct drug prod - ucts: Identity confirmation, impurity detection or quantification and quan - tification of an active compound. As outlined above, in molecular genetics, we work with DNA and RNA sequences and with sequence counts and concentrations of DNA and RNA molecules, which simplifies the task if for example compared with poorly defined drug products arising from complex chemical or biological syn - thesis workflows. Accordingly, we design the experimen - tal workflow accompanied by appro - priate documentation to meet the reg - ulatory requirements. The foundation for the formal reporting is represented by our quality management system with the ISO 9001:2015 and EN ISO 13485:2016 certifications, the accredi - tation according to ISO/IEC 17025:2017 (STS 0429) for Sanger Sequencing, Next Generation Sequencing and Fragment Length Analysis and the GMP Compliance issued by Swissmedic for our Sanger Sequencing department. Processes are clearly defined, vali - dated, and controlled, and described in procedures and Standard Operating Procedures (SOPs), which are reviewed periodically. Instruments are qualified with periodic re-qualification periods, and corresponding instrument test documents are archived. Changes that affect the quality are validated. In cases where the quality cannot be covered by verification, the produc - tion process is validated. Operators are trained regularly in practical work and documentation procedures. All lab - oratory processes, including the bio - informatic analyses, are documented in lab data sheets, where time and date, operator, working procedures, reagent lot numbers and machine serial numbers are recorded. Finally, a summary report is produced describ - ing the findings with reference to all primary data and analysis. The doc - umentation and related records are maintained in a controlled manner. This includes the approval and release by our quality assurance unit. Below we will describe a few cases to illus - trate our approaches. These analytical procedures are sup - ported by our isolation services that perform DNA and RNA extractions from diverse matrices including envi - ronmental samples such as soil or air, animal and plant tissue biopsies, stool, blood and urine samples, to name a few (see Figure 2 ). Furthermore, primers and oligos needed for NGS and PCR can be synthesized in house, which facilitates shorter production timelines and flexibility. Microsynth AG, SwitzerlandSch?tzenstrasse 15 ? P.O. Box ? CH - 9436 Balgach ? Phone + 41ff71ff722ff83 33 ? Fax + 41ff71ff722ff87 58 ? info @microsynth.ch ? www.microsynth.com THE SWISS DNA COMPANY White Paper ? Next Generation Sequencing Case 2: Transgene Copy Number in Production Strains Production of some vaccines are based on the production of specific proteins, for which transgenic pro - duction strains are used. One of the requirements is to confirm that the copy number of the transgene is stable through the production process. In the early development step, Microsynth designed and tested the functional - ity of a duplex dPCR assay to measure transgene copy number for the respec - tive vaccine program of the sponsor. In a second step, reference material was constructed and qualified before a full qualification was run address - ing the parameters: specificity (spe - cific amplification of locus and matrix effects), accuracy, intermediate preci - sion, repeatability, linearity, and range, as well as limit of detection and limit of quantification. Results of the study were reported in a qualification report. Case 3: Measuring CRISPR/Cas9 Off-Target Editing Although CRISPR/Cas9 editing is far more precise than previous genome editing technologies, some off-target editing may occur and must be tested in drug products. The editing rates observed in the off-target loci are sig - nificantly lower than for the on-tar - get locus. Thus, accurate and precise measurements below 2 % editing rates are required, which is challeng - ing. The method of choice for such low-frequency editing rates is ampli - con deep-sequencing. Based on dis - cussions with our sponsor we qual - ified and validated the amplicon sequencing strategy that included an elaborated robustness testing and the validation of the method against pre-defined criteria set by the sponsor. Case 1: Sequence Stability of a Bacterial Production Strain To verify that no unwanted mutations accumulated in a bacterial produc - tion strain, the genomes of the refer - ence master strain and several derived production strains were determined. For this, a long-read next generation sequencing approach with PacBio was chosen in parallel with short-read Illumina sequencing. The long reads, up to about 30 kb in length, were used to produce the de novo chromo - some assemblies. In parallel, Illumina short reads were generated and used to reduce the remaining sequenc - ing errors in the contigs. The final sequencing contig of the reference master strain was then used to identify and confirm the species identity, using average nucleotide identify and digital to digital sequence hybridization strat - egies. Publicly available database resources provided the references. Finally, the newly produced genome sequences from the strains in the pro - duction process were compared to the genome of the reference strain. Any nucleotide changes were listed according to position. These bioinfor - matic analyses have confirmed that no unwanted mutations arose during the production process. Conceptually, this task may be regarded as identity test, where identity refers to the genome sequence of the test item. Contact Hopefully, we have been able to provide you with a better understanding how we can help you with your projects and we are looking forward to advising you and designing a work procedure to support your research or drug product develop - ment. To request information or arrange to visit Microsynth, please contact us at: firstname.lastname@example.org Microsynth AG, SwitzerlandSch?tzenstrasse 15 ? P.O. Box ? CH - 9436 Balgach ? Phone + 41ff71ff722ff83 33 ? Fax + 41ff71ff722ff87 58 ? info @microsynth.ch ? www.microsynth.com THE SWISS DNA COMPANY White Paper ? Next Generation Sequencing
16S metagenomics powers human, animal, and environmental microbiome studies of any scale. Dynamic host-microbe interactions have shaped the evolution of life. Virtually all plants and animals are col - onized by microbiota, which are eco - logical communities of commensal, symbiotic, and pathogenic microor - ganisms. And it is increasingly recog - nized that the biological processes of hosts and their associated micro - bial communities function in tandem, often as biological partners forming a collective entity known as a metaor - ganism . Microorganisms form very diverse communities and a character - istic of these communities is that a few taxa dominate them, while a very large number of taxa occur with lower frequency . Furthermore, taxa that cannot be cultivated may also occur and therefore such taxa cannot be detected by classical methods. The rapidly growing interest in micro - biome research has been reinforced by the ability to profile different microbial communities using Next Generation Sequencing (NGS). This culture-free, high-throughput technology enables the identification and comparison of entire microbial communities, which is known as metagenomics . Metagenomics typically involves two different sequencing strategies: the first sequencing strategy is amplicon sequencing, which is usually of the 16S rRNA gene as a phylogenetic marker, while the second sequencing strategy is shotgun metagenome sequencing, and this is a whole genome sequenc - ing approach . Therefore, metagen - omics provides comprehensive answers to a range of important ques - tions, including the influence of the human intestinal flora on health. The use of the 16S ribosomal RNA gene in prokaryotes and the ITS sequence (internal transcribed spacers of rDNA) in fungi as phylogenetic markers has proven to be an efficient and cost-ef - fective strategy for microbiome anal - ysis. In fact, experiments revolving around 16S rRNA allow even the impu - tation of functional contents based on taxon frequencies  . On the other hand, shotgun metagen - omics enables researchers to measure the functional relationships between hosts and bacteria by directly deter - mining the functional content of samples. In addition, shotgun metagenomics has a theoretically unbiased coverage of all taxonomies found in a DNA sample. However, contamination with host DNA and the occurrence of low frequency taxa requires very deep sequencing if one is to achieve the same taxonomic res - olution as 16S rRNA sequencing. This means a manifold increase in both the costs and the data load. In this White Paper we will limit ourselves to 16S amplicon sequencing and the factors that need to be taken into account when conducting it. Amplicon Metagenome Analyses of Microbial Communities – Doing It the Right Way Microbiota and NGS - a Dream Team Typical Barcoding Loci for Bacteria and Fungi 16S rDNA as barcoding locus in prokaryotes The 16S rRNA gene is the DNA sequence corresponding to ribosomal RNA and it is essential for the synthe - sis of all prokaryotic proteins. The 16S rRNA gene occurs in all bacteria and it is highly conserved and highly spe - cific. The internal structure of the 16S rRNA gene is composed of variable regions (see Figure 1 ). Having varying Microsynth AG, SwitzerlandSchützenstrasse 15 ? P.O. Box ? CH - 9436 Balgach ? Phone + 41fi71fi722fi83 33 ? Fax + 41fi71fi722fi87 58 ? info @microsynth.ch ? www.microsynth.ch THE SWISS DNA COMPANY White Paper ? Next Generation Sequencing Figure 1: Overview of ribosomal gene loci commonly used for the taxonomic analysis of microbial communities. Hypervariable regions are marked in green, while conserved regions are marked in gray. A. Structure of the prokaryotic 16S rRNA gene showing the nine hypervariable regions (V1-V9) and the regions targeted by the commonly used primer systems. B. Organization of the fungal rRNA gene operon showing two internal transcribed spacer regions (ITS). ITS2 is used most often for profiling fungal communities. C. 3D structural model of the 16S rRNA of Escherichia coli according to Tung et al . The variable regions in the 16S rRNA are shown in green. D. Secondary structure of the 16S rRNA with variable regions in green. Choosing the Right Primer Set is the Key to Success! Amplicon metagenomics is based on NGS sequencing of the microbial 16S rRNA gene. Since NGS single read lengths are limited to 300 base pairs (600 bp for paired end reads) when using Illumina high-throughput plat - forms, only parts of the 16S rRNA gene can be amplified and sequenced. In prokaryotes, the analysis targets hypervariable regions (V1-9) on the 16S rRNA gene. Meanwhile, in fungi the internal transcribed spacer regions (ITS) are used for taxonomic profiling (see Figure 1 ). For 16S/ITS amplicon metagenom - ics, it is important to give high prior - ity to the choice of primers. An ideal primer system should be sufficiently universal to cover a broad range of taxonomic groups, while the result - ing amplicon must provide sufficient taxonomic information for a reliable taxonomic classification. Based on our experience and the validation of our 16S/ITS analysis pipeline, we rec - ommend the V34 primer system for a broad and accurate bacterial classifi - cation. However, if Archaea are also expected, the V4 primer system should be used in order to obtain a good tax - onomic classification. It should be emphasized that our service is not limited to the presented marker genes and primer systems; other phyloge - netic marker genes (e.g. cytochrome c oxidase I) and primer systems can also be used. Furthermore, a pilot study can be very helpful in terms of finding the best primer system for your specific research question. Finally, metagen - ome analyses should only compare communities generated with identi - cal primer sets. This is because of the biases of the different primer systems. Besides the choice of the locus specific PCR primers, the isolation of high-qual - ity DNA from environmental samples has a major impact on the outcome of the study. 5 C D ITS regions as barcoding locus for fungi The ITS region has become the gold standard for the classification of fungi . With few exceptions , this locus is suitable for distinguishing fungi up to species level. In addition to the ITS regions, other loci have been used for barcoding fungi, although the data basis is much smaller . degrees of difference among the dif - ferent bacteria makes it possible to identify the taxonomic identity of microbes, at the genus level and often at the species level. Since it is not prac - tical to sequence the complete 16S rDNA using NGS, only a part of the vari - able regions is sequenced. Microsynth currently offers different standard primer sets that have been developed based on the recommen - dations of the Human Microbiome Project Consortium . Specifically, the V4 and V34 locus primers are suit - able for most bacterial metacom - munity projects. It has been demon - strated in several studies that the aforementioned primers facilitate the detection of a broad range of taxa (see Figure 1A ). Depending on the project requirements, customer-spe - cific primer sets can also be applied or even developed and validated. Microsynth AG, SwitzerlandSchützenstrasse 15 ? P.O. Box ? CH - 9436 Balgach ? Phone + 41fi71fi722fi83 33 ? Fax + 41fi71fi722fi87 58 ? info @microsynth.ch ? www.microsynth.ch THE SWISS DNA COMPANY White Paper ? Next Generation Sequencing The first step in an amplicon metage - nome project is deciding which primer set is the most promising. At Microsynth, the question of whether to work with a standard primer set or to instead develop a customer-spe - cific primer set is discussed in detail with the customer. In addition, it must be defined whether DNA is to be iso - lated internally or whether it should be outsourced (see Figure 2 ). The DNA is then amplified by PCR and Microsynth uses a “two-step” PCR protocol for the amplification. In a first step, the locus is amplified with short template spe - cific primers as well as an Illumina tail adapter. From there, in a second step, the so-called NGS fusion primers, including an index for multiplexing as well as an Illumina adapter, are used. Previous studies have shown that this protocol generates high quality mul - tiplex amplicon libraries and ensures high reproducibility . Instead of only using a single forward and reverse primer for first step ampli - fication, some protocols use several forward primers that differ in length by adding various numbers of degen - erate bases (wobbles, Ns) at the 5’ end of the locus specific primer. An alter - native but similar approach is to use a fixed number of degenerate bases (see Figure 3 ). Both concepts aim at adding sequence diversity as this improves the quality and quantity of reads gen - erated on an Illumina MiSeq platform (see Figure 4 ). The fixed length degen - erate bases are less effective in terms of introducing sequence diversity compared to the staggered degen - erate base approach. However, they represent a good trade-off in practice and are also easier to handle in down - stream analysis. These protocols are especially useful for high-throughput projects where sequencing through - put is particularly critical and many samples are pooled. For projects involving very low amounts of starting material we rec - ommend a three-step PCR protocol including two subsequent locus-spe - cific PCRs to increase the yield of sequenceable amplicons. After equi - molar pooling of the PCR products, NGS sequencing is performed on the Illumina MiSeq. Meanwhile, the final and perhaps most important step is the bioinformatic analysis. For this step, we have established a designated pipeline that comprises state-of-the- art algorithms and software designed to extract as much valuable informa - tion as possible from the generated data and to visualize the data in a cap - tivating form. In the following section we will show in more detail how a bio - informatic analysis and its output in metagenome projects can look. What Does a Typical Project Schedule Look Like? 16S/ITS Metagenomics AnalysisProject Output: Total DNA Isolation Second Step PCR Illumina MiSeq Sequencing Option I: Samples Option II: Isolated DNA Project Input: Report Generation Option IV: Bioinformatics only Experimental Design Option I: Library Prep only Option II: Raw Data only Option III: Full Report First Step PCR with Custom or Standard Primer Set Option III: First Step Products Figure 2: Schematic representation of a project procedure for metagenome analysis of microbial commu - nities. Depending on the initial situation and the problem, the first step is to determine the suitable primer set. However, should the customer request it, a new primer set can be developed. Furthermore, either the entire process - including DNA isolation - can be outsourced to Microsynth, or the DNA can be isolated by the customer. At the end of the process the customer will receive a clearly structured report that can be used for further analysis. Figure 3: Principle of the degenerate base approach for primers. A: In the first step PCR, the target is amplified and the tail adapter is appended. 5 degenerate bases are appended between the tail adapter and the locus specific primer. B: In the second step PCR the index and the adapter are appended. The second PCR product binds to the Illumina flow cell and it is sequenced starting at the degenerate bases, which ensures sequence diversity. A B f o rw ard prim er l o cu s sp eci? c r e ver se prim er l o cu s sp eci? c deg en erate bases d eg en erate bases t a il a d ap ter t a il a d ap ter in dex a d ap ter ad ap ter i n dex Microsynth AG, SwitzerlandSch?tzenstrasse 15 ? P.O. Box ? CH - 9436 Balgach ? Phone + 41 71 722 83 33 ? Fax + 41 71 722 87 58 ? info @microsynth.ch ? www.microsynth.ch THE SWISS DNA COMPANY White Paper ? Next Generation Sequencing State of the Art - the Bioinformatics Analysis Pipeline from Microsynth For the bioinformatic analysis of the sequencing data, the sequenced paired-end reads are first subjected to de-multiplexing and trimming of Illumina adaptor residuals. In a second preparation step, paired-end reads are filtered for their quality and their locus specific primers are trimmed as well. From there, the remain - ing paired-end reads are de-noised  to form operational taxonomic units (OTUs), while in the process dis - carding singletons and chimeras. The resulting OTU abundances are then filtered for possible barcode bleed-in contaminations  to reduce noise. Following this, the OTU sequences are compared to a reference sequence database, such as RDP , in order to predict their taxonomies and cor - responding confidence scores. The resulting metagenome is visualized by an interactive Krona chart  (see Figure 5 ) that provides a quick and easy overview of the data. This enables the scientist to intuitively explore the intricacies of the analyzed bacte - rial community. The diversity of the metagenomic community is expressed in simple and comparable terms as alpha and beta diversity scores. The alpha diversity describes the intra-di - versity of each sample, while the beta diversity describes the inter-diversity of all samples together . Different and widely used alpha diversity scoring metrics are displayed in Figure 6B . On the X axis the analyzed samples are annotated, and on the Y axis their individual scores for each metric are displayed. Rarefaction curves are cal - culated in order to estimate if a micro - biome has been sufficiently character - ized. If the curves end in a plateau, this signifies that the microbiome was suf - ficiently covered (see Figure 6A ). The complex interaction of multiple bac - terial communities in a given envi - ronment is described by beta diver - sity based on a distance metric such as Unifrac . Principal component analysis (PCA) helps in terms of simpli - fying, understanding, and visualizing such interactions (see Figure 7A ). In Figure 4: These charts show the effect of degenerate bases on the quality of the sequencing. A: In the chart of the sequence content across all bases, you can clearly see the 5 degenerate bases at the beginning of the sequence due to their typical distribution (approximately 25%). B: When no degenerate bases were included, the beginning of the sequencing was always the same. C: The chart of the per base quality shows high quality scores for all bases when degenerated bases were used. D: When no degenerate bases were used in the primers, the quality score soon decreased for longer reads. A B C D Microsynth AG, SwitzerlandSchützenstrasse 15 ? P.O. Box ? CH - 9436 Balgach ? Phone + 41fi71fi722fi83 33 ? Fax + 41fi71fi722fi87 58 ? info @microsynth.ch ? www.microsynth.ch THE SWISS DNA COMPANY White Paper ? Next Generation Sequencing ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ??? ???????? ??????? ? ??????? ? ??? ????? ? ????? ? ????? ???? ??? ? ?? ? ?? ???? ?????? ? ? ? ?? ? ? ? ? ??? ?? ? ? ? ? ??? ?? ??? ????? ??????? ??????? ??????? ??????? ??????? ??????? ??????? ??????? ??????? ??????? ??????? ??????? ??????? ??????? ??????? ??????? ??????? ??????? ??????? ? ? ? ??? ? ?? ? ?? ??? ??? ??? ? ?? ? ?? ??? ??? ??????? ????????? ??? ??? ??!??? ?"?? ?????????? ???????????? ?????????? ??# Figure 6. Examples of alpha diversity results. 6A. Rarefaction curves indicating whether sampling and sequencing covered the sample richness (the x axis displays the sampled number of reads, while the y axis displays the number of detected OTUs). 6B. Alpha diversity measures for the analyzed community including observed rich - ness; the Chao 1 index and the Shannon diversity index. Figure 5. Interactive Krona chart of the bacteria represented by 16S rRNA gene amplicon-based bac - terial diversity in a feces sample. Each circle repre - sents the phylum, class, order, family, genus, and species from the inside to the outside of the circle, respectively. In addition, the relative abundance of each taxa is annotated on the chart. Figure 7A , the PCA was able to explain 90% of the variance of the original data with just two components (75% on the first principal component and 15% on the second principal component). If an experimental design exists, dividing samples into different categories such as treated and control samples, the dif - ferential OTU analysis reveals detailed changes in the microbiome of the analyzed groups  (see Figure 7B ). Finally, functional profiles are pre - dicted  (see Table 1 ) using various publicly available databases. The path - ways and their abundance within the different samples are shown in Table 1 . Microsynth AG, SwitzerlandSchützenstrasse 15 ? P.O. Box ? CH - 9436 Balgach ? Phone + 41fi71fi722fi83 33 ? Fax + 41fi71fi722fi87 58 ? info @microsynth.ch ? www.microsynth.ch THE SWISS DNA COMPANY White Paper ? Next Generation Sequencing Conclusion The complexity of metagenome analysis has increased in line with technological progress. In order to perform meaningful metagenome analyses, our experience has taught us that the following success criteria are important: • It must be considered which variable DNA region (e.g. on the 16S rDNA or ITS regions) is best suited for the intended study. Based on these considerations, the optimal primer set is determined (and, if possible, it is pre-tested in a pilot study). • To be able to amplify the different taxa representatively and to sequence them afterwards, a robust and functional DNA isolation procedure must be available. On the other hand, we recommend a “two-step” protocol if possible, to enable the use of high-quality amplicon libraries for the subsequent sequencing. • Data analysis should be performed using a few but meaningful bioinformatics tools. • If you are lacking experience in one or more of the above criteria, we recommend outsourcing the study to an experi - enced service provider. Microsynth has more than 10 years of experience. pathwa yd escrip ?o nS ample_ V3 4_1a Samp le_V 34_1 bSample_ V3 4_1c NO NOXIPE NT-PWY pentos e phospha te pa thwa y (n on -oxida ?v e br an ch)4 55004630 04 6500 CA LVIN-PWY Calvin -B en son- Bassha m cycl e3 9700 4020 04 0400 PW Y-7220 aden osine de oxyribonuc leo? des de novo biosynth esis II 397003 9800 40100 PW Y-7222 guanosine de oxyribonuc leo? des de novo biosynth esis II 397003 9800 40100 PW Y-7663 gondo ate bi osynth esis (a na erob ic )3 8200 3860 03 8800 PW Y-6737 starch de grad a? on V3 7400 3750 03 7800 PW Y-5101 L-isol eu cine bi osynth esis II 371003 7800 37800 GLYC OCAT-PWY glyc og en de grad a? on I (b ac terial )3 6800 3760 03 7300 PW Y-7229 superpathw ay of ad en osine nuc leo? des de novo biosynth esis I3 6500 3700 03 7200 ANAG LYCO LYSIS- PWYg lyco lysis III (fro m gluc ose) 361003 6600 36700 Showing 1 to 10 of 336 entrie s Table 1. Functional profiles predicted according to OTUs, their predicted taxonomies, and their abundance in each of the samples. ?? ?? ?? ???? ? ? ?? ? ? ?? ? ? ?? ???? ?? ?? ? ?? ??? ?? ?? ????? ?? ?????? ?? ?? ?? ???????? ??? ??? ? ??? ?? ???? ?? ???? ?? ???? ?? ???? ?? ???? ?? ???? ?? ?? ?? ?!?" ?????#? ?? ???? ?? ???? ???? ???? ?$? ???? ????%?? ???& ?? ?? ?'?(?)? ???*??+? ??*??, ?? ??'?*?'?-?, ?*??(? ????- ?*??? ??? ?? ???(?' ?-??? ?*?+?)?' ??*??) ?)? ???*?-?? ?*?-?'? ??,?? ?*?(?)? ???( ?? ?? ?'??? ??*??)?'? ?*??-???,?*??'? ?*??(? ???-? ?*??(? ???- ?? ??, ?-?'?? ???*??+?) ??*?? ?'? ??)?*??? ?*??)? ???? ?*?)?(? ??? ?? ??- ?-??)? ??*??)?,? ?*???)?(?(?*?+?(? ?*??? ????, ?*?-?? ??? ?? ??' ?,?'?? ???*??? ??*?? ?? ???*???' ?*??'? ???)? ?*??'? ???' ?? ??) ??'?-? ???*?-?'?+ ??*??- ?,?' ????*?'? ?(?*??+ ????) ?,?*?+? ????' ?? ??+ ???(? ??*???-? ?*??-?,??-?*?+?? ?*?,?-? ???)? ?*?)?+? ???) ?? ??? ? ?? ?? ?? ??? ??? ?? ?? ??? ?????????? ?? ?? ??? ?????????? ??? ? ????????? ? ????????? ? ????????? ??? ??? ??? ??? ??? ??? ? ?? ? ?? ? ?? Figure 7. Examples of beta diversity results. 7A. Principal component analysis plot to visualize sample clustering. 7B. This excerpt from a results table shows differ - ential abundance of OTUs between two conditions, including statistical measures for differential abundance (log fold change) and significance (adjusted p-value). Microsynth AG, SwitzerlandSchützenstrasse 15 ? P.O. Box ? CH - 9436 Balgach ? Phone + 41fi71fi722fi83 33 ? Fax + 41fi71fi722fi87 58 ? info @microsynth.ch ? www.microsynth.ch THE SWISS DNA COMPANY White Paper ? Next Generation Sequencing Literature  Rausch, P., Rühlemann, M., Hermes, B.M. et al. Comparative analysis of amplicon and metagenomic sequenc - ing methods reveals key features in the evolution of animal metaorganisms. Microbiome 7, 133 (2019). https://doi. org/10.1186/s40168-019-0743-1  McGill, B.J., Etienne, R.S., Gray, J.S., Alonso, D., Anderson, M.J., Benecha, H.K., Dornelas, M., Enquist, B.J., Green, J.L., He, F.L., Hurlbert, A.H., Magurran, A.E., Marquet, P.A., Maurer, B.A., Ostling, A., Soykan, C.U., Ugland, K.I. & White, E.P. (2007) Species abundance distributions: moving beyond single prediction the - ories to integration within an ecologi - cal framework. Ecology Letters, 10: 995– 1015.  Hugenholtz, P. (2002) Exploring prokaryotic diversity in the genomic era. Genome Biology 3: reviews0003.1– reviews0003.8.  Morgan XC, Huttenhower C. Chapter 12: human microbiome analysis. PLoS Comput Biol. 2012;8(12):e1002808.  Langille MGI, Zaneveld J, Caporaso JG, McDonald D, Knights D, Reyes JA, Clemente JC, Burkepile DE, Vega Thurber RL, Knight R, et al. Predictive functional profiling of micro - bial communities using 16S rRNA marker gene sequences. Nat Biotechnol. 2013;31(9):814–21.  The Human Microbiome Project Consortium (2012) A framework for human microbiome research. Nature, 486: 215-221.  Schoch CL, Seifert KA, Huhndorf S, Robert V, Spouge JL, Levesque CA, Chen W, Bergeron MJ, Hamelin RC, Vialle A, and Fungal Barcoding Consortium. (2012) Nuclear ribosomal internal tran - scribed spacer (ITS) region as a uni - versal DNA barcode marker for Fungi. Proceedings of the National Academy of Science 109: 6241-6246. (doi: 10.1073/ pnas.1117018109)  Grünig, C.R.; Brunner, P. C.; Duo, A. & Sieber, T. N. (2007) Suitability of methods for species recognition in the Phialocephala fortinii - Acephala appla - nata species complex using DNA analy - sis. Fungal Genetics and Biology, 44: 773- 788.  Ratnasingham S, Hebert PDN (2013) A DNA-Based Registry for All Animal Species: The Barcode Index Number (BIN) System. PLoS ONE 8(8): e66213. DOI:10.1371/journal. pone.0066213  Tung, C.-S., Joseph, S. & Sanbonmatsu, K.Y. (2003) All-atom homology model of the Escherichia coli 30S ribosomal subunit. Nature Structural Biology, 9: 750-755  Berry, D., Mahfoudh, K.B., Wagner, M. & Loy, A. (2011) Barcoded primers used in multiplex ampli - con pyrosequencing bias amplifi - cation, Applied and Environmental Microbiology, 77: 7846- 7849.  R.C. Edgar (2016), UNOISE2: improved error-correction for Illumina 16S and ITS amplicon sequencing, https://doi.org/10.1101/081257  R.C. Edgar (2018), UNCROSS2: identification of cross-talk in 16S rRNA OTU tables, https://doi. org/10.1101/400762  Cole, J. R., Q. Wang, J. A. Fish, B. Chai, D. M. McGarrell, Y. Sun, C. T. Brown, A. Porras-Alfaro, C. R. Kuske, and J. M. Tiedje. 2014. Ribosomal Database Project: data and tools for high through - put rRNA analysis Nucl. Acids Res. 42(Database issue):D633-D642; doi: 10.1093/nar/gkt1244 [PMID: 24288368]  Ondov BD, Bergman NH, and Phillippy AM. Interactive metagenomic visualization in a Web browser. BMC Bioinformatics. 2011 Sep 30; 12(1):385.  https://journals.plos.org/ plosone/article?id=10.1371/journal. pone.0061217  Lozupone C, Knight R . (2005). UniFrac: a new phylogenetic method for comparing microbial communities. Appl Environ Microbiol 71: 8228–8235.  https://genomebiology. biomedcentral.com/articles/10.1186/ s13059-014-0550-8 (DESeq2)  Predictive functional profil - ing of microbial communities using 16S rRNA marker gene sequences. Langille, M. G.I.*; Zaneveld, J.*; Caporaso, J. G.; McDonald, D.; Knights, D.; a Reyes, J.; Clemente, J. C.; Burkepile, D. E.; Vega Thurber, R. L.; Knight, R.; Beiko, R. G.; and Huttenhower, C. Nature Biotechnology, 1-10. 8 2013. Microsynth AG, SwitzerlandSch?tzenstrasse 15 ? P.O. Box ? CH - 9436 Balgach ? Phone + 41 71 722 83 33 ? Fax + 41 71 722 87 58 ? info @microsynth.ch ? www.microsynth.ch THE SWISS DNA COMPANY White Paper ? Next Generation Sequencing Contact Microsynth AG Schützenstrasse 15 CH-9436 Balgach Switzerland phone: +41-71-722 83 33 web: www.microsynth.ch email: email@example.com Microsynth AG, SwitzerlandSchützenstrasse 15 ? P.O. Box ? CH - 9436 Balgach ? Phone + 41fi71fi722fi83 33 ? Fax + 41fi71fi722fi87 58 ? info @microsynth.ch ? www.microsynth.ch THE SWISS DNA COMPANY White Paper ? Next Generation Sequencing
Économisez du temps et de l’argent Évitez les extractions de plasmides inutiles, longues et coûteuses à partir de clones infructueux. Accélérez vos recherches d’une journée entière. Simple Déposez simplement vos colonies d’E. coli dans une boîte de dépôt Microsynth en fin d’après-midi et recevez votre résultat le lendemain avant 14 heures (tubes) ou à partir de 15 heures (plaques). Robuste et versatile Meilleur résultat possible grâce à un procédé robuste et standardisé développé pour une efficacité maximale. Idéal pour les plasmides difficiles. Ne se limite pas à E. coli . Ecoli NightSeq® - Nouveau Service Innovant Microsynth France SAS170 Av. Gabriel Péri ? 69120 Vaulx-en-Velin ? Phone +33 4 37 45 02 96 ? info @microsynth.fr ? www.microsynth.com WE ENRICH YOUR RESEARCHFlyer ? Sanger Sequencing Simple 1. Inoculez votre colonie d’ E. coli ou votre ADN plasmidique dans le tube/plaque fourni. 2. Déposez vos échantillons dans l’une de nos boîtes de dépôt d’échantillons ( aucune incubation n’est nécessaire ). 3. Vos résultats de séquençage seront disponibles le lendemain avant 14 heures (tubes) ou à partir de 15 heures (plaques) Vous n‘avez jamais essayé ? Écrivez un courriel à firstname.lastname@example.org et demandez des étiquettes gratuites . Comment commander ? Entrez dans notre boutique en ligne via www.microsynth.com Cliquez sur „ Order Labels “ dans la zone verte „Sanger Sequencing“. Cliquez sur le service „ Ecoli NightSeq “ de votre choix et suivez les instructions. Vous avez besoin de plus d‘informations ? Appelez-nous au +33 437 45 02 96 ou Envoyez-nous un e-mail à email@example.com Produits Ecoli NightSeq® (lot de 50 étiquettes et tubes prépayés*) Ecoli NightSeq® (lot de 50 étiquettes et tubes non prépayés*) Ecoli NightSeq® (1 étiquette prépayée et une plaque à 96 puits*) Ecoli NightSeq® (1 étiquette non prépayée et une plaque à 96 puits*) * Les tubes et les plaques seront fournis gratuite - ment avec notre solution tampon (propriété exclu - sive). “Grâce au nouveau service Ecoli NightSeq de Microsynth, nous sommes désormais en mesure de séquencer en format haut débit et gagner jusqu’à deux jours par rapport au service précédent. La facilité de préparation des échantillons et la haute qualité des séquences nous ont convain - cus.” Andreas Lehman, Molecular Partners AG Qu’est-ce que l’Ecoli NightSeq® ? L’Ecoli NightSeq® est un nouveau service de Microsynth innovant . En utilisant ce service, vous pouvez écon - omiser du temps de manipulation au laboratoire et réduire considéra - blement vos dépenses sur les kits de purification de l’ADN plasmidique en isolant uniquement les plasmides des clones présentant le résultat de séquençage souhaité. Au lieu d’isoler le plasmide vous-même, vous pouvez directement prélever la colonie et l’envoyer à Microsynth. Le lende - main, vous avez déjà vos résultats de séquençage. Vous pouvez maintenant poursuivre avec les clones réussis que vous avez incubés pendant la nuit. De cette manière vous pouvez accélérer vos recherches d’une journée entière . En outre, au-delà d’E. coli, d’autres organismes (principalement des bactéries gram-négatives) ou de très faibles quantités d’ADN plasmidique (?5 ng dans 1 µl) peuvent être utilisés. Figure 1: Comparaison de l’approche conventionnelle avec la nouvelle approche Ecoli NightSeq®. Envoyez-nous directement votre colonie d’E. coli (ou d’autres organ - ismes, principalement des bactéries gram négatives). Après avoir reçu les résultats du séquençage, isolez uniquement les plasmides des clones concernés et gagnez un jour supplémentaire. Ecoli NightSeq® Approach Conventional Approach Customer Microsynth Picking Day 1 Day 2 Day 3 Ecoli NightSeq Incubate picked colonies Downstream Picking Incubate picked colonies Prep Sequencing Time gain Downstream - Gain 1 full day - Only prep successful clones WE ENRICH YOUR RESEARCHFlyer ? Sanger Sequencing Microsynth France SAS170 Av. Gabriel Péri ? 69120 Vaulx-en-Velin ? Phone +33 4 37 45 02 96 ? info @microsynth.fr ? www.microsynth.com
Délais d’exécution rapides Pour les services de nuit, livraison des résultats tôt le lendemain matin avant le début de votre travail, du lundi au samedi. Résultats de haute qualité Jusqu’à 1’100 bases ou plus en qualité Phred20 pour les échantillons de routine mais aussi les plus difficiles à séquencer en plasmide et PCR. Respect de l’environnement Vos échantillons de séquençage sont principalement expédiés par des moyens de transport respectueux de l’environnement (train, vélo). Economy Run - Le Meilleur Service Sanger WE ENRICH YOUR RESEARCHFlyer ? Sanger Sequencing Microsynth France SAS170 Av. Gabriel Péri ? 69120 Vaulx-en-Velin ? Phone +33 4 37 45 02 96 ? info @microsynth.fr ? www.microsynth.com Vous n‘avez jamais essayé ? Écrivez un courriel à firstname.lastname@example.org et demandez des étiquettes gratuites. Vous avez besoin de plus d‘informations ? Appelez-nous au +33 437 45 02 96 ou Envoyez-nous un courriel à email@example.com Aperçu de l’Economy Run L’Economy Run est un service de séquençage Sanger en tubes et plaques pour les plasmides et les produits PCR. Il comprend diverses fonctions complé - mentaires utiles et est disponible en version prépayée ou non prépayée. Le service prépayé est très populaire en raison de son excellent rapport qual - ité-prix . Produits Economy Run (lot de 50 étiquettes prépayées) Economy Run (lot de 50 étiquettes non prépayées) Economy Run Plus (1 étiquette prépayée et une plaque à 96 puits) Economy Run (1 étiquette prépayée et une plaque 96 puits)* Caractéristiques spécifiques du service Economy Run Tu b e Prépayé Economy Run Tu b e Non prépayé Economy Run Plus Plate Prépayé Economy Run Plate Prépayé Economy Run Plate Non prépayé Unité d’achat lot de 50 éti - quettes par réaction 1 étiquette plaque 1 étiquette plaque par réaction Séquençage de nuit 1 X X Purification PCR en amont X2 X2 Inclus X2 Isolement initial des plasmides d’ E.coli inclus Inclus X2 Rendu résultats suite à la réception de l’échantillon Lu - Sa Lu - Sa Lu - Sa Lu - Sa Lu - Sa avant 8 hrs jour suivant avant 8 hrs jour suivant avant 8 hrs jour suivant 3 avant 8 hrs jour suivant 3 avant 8 hrs jour suivant 3 Stockage des amorces (sur liste d’amorces personnalisées) 4 mois (10 mois) 4 mois (10 mois) 4 mois (10 mois) 4 mois (10 mois) 4 mois (10 mois) Stockage échantillon 4 jours ouvrables 4 jours ouvrables 1 mois 1 mois 1 mois Séquençage multiple à partir d’un tube/une plaque sur demande sur demande X X X Prélèvement de colonies à partir de plaques d’agar dans des plaques à 96 puits et génération de stocks de glycérol X2 X2 Isolation de plasmides à plus grande échelle (Midi/ Maxi) à partir de clones sélectionnés X2 X2 Expédition des plasmides isolés au client X2 X2 1) Nécessite une boîte de dépôt d’échantillons Microsynth à proximité avec une logistique de nuit. 2) Des frais supplémentaires s’appliquent 3) Applicable aux échantillons purifiés qui arrivent dans nos locaux en début de matinée (pas de séquençage de nuit possible). Caractéristiques et avantages Longueur de lecture jusqu’à 1’100 bases et plus- Des amorces standards seront ajoutées gratuitement – Synthèse interne d’amorces de séquençage spéci - fiques - Processus d’enregistrement des échantillons intuitif, convivial et rapide via notre portail en ligne - Possibilité d’affiner les paramètres d’analyse du logiciel de séquençag e afin d’obtenir les performances souhaitées - Accès direct à une assistance technique avec un personnel académique expérimenté - Outils en ligne utiles vous permettant de superviser votre stock d’étiquettes à code-barres et d’amorces mais aussi de le partager entre les membres de votre groupe - Tous les résultats peuvent être téléchargés , les chromatogrammes peuvent être visualisés et édités. *Pour la version non prépayée des plaques, Microsynth n’a pas besoin d’étiquettes de plaques. L’étiquetage manuel de vos plaques 96 puits est suf - fisant. WE ENRICH YOUR RESEARCHFlyer ? Sanger Sequencing Microsynth France SAS170 Av. Gabriel Péri ? 69120 Vaulx-en-Velin ? Phone +33 4 37 45 02 96 ? info @microsynth.fr ? www.microsynth.com
Quels sont les avantages d'une collaboration avec Microsynth ?
Une collaboration avec Microsynth, fournisseur de séquençage NGS pour un séquençage fiable et une analyse appronfondie des données, offre de nombreux avantages aux professionnels. Cette collaboration permet l'obtention de données de séquençage de nouvelle génération fiables et de haute qualité, ainsi qu'une analyse entièrement personnalisée rendue possible grâce à l'équipe interne de bioinformaticiens.
L'entreprise dispose d'une grande expérience dans une large gamme d'applications de séquençage de nouvelle génération et permet la réalisation de projets complets, allant de l'isolement des acides nucléiques à l'analyse bioinformatique. Les modules d'analyse bioinformatique auto-développés permettent d'exploiter un maximum d'information des données de séquençage récoltées.