Re-Sequencing of Eucaryotic Model Organism


You work with human or model organ­isms such as for example mice, rat, or C. elegans and you want to know the ge­netic variation in your specimens? Whole genome re-sequencing is getting easier and affordable by the advent of the new­est sequencing technologies and the availability of well curated reference ge­nomes. This allows you to understand (i) how genetic differences affect health, al­lows you to perform (ii) population stud­ies, (iii) do molecular breeding for func­tional gene or marker detection and much more. Microsynth offers a “one-stop service” for the re-sequencing of model organisms starting from DNA iso­lation to data analysis to detect the ge­nome-wide variation in your specimens. Results are reported in user-friendly out­puts and can be directly used in your re­search. Due to the availability of the flex­ible and scalable Illumina NextSeq and MiSeq platforms, Microsynth can offer its customers an optimized sequencing strategy for every study (see also the application note "ReSeq_Models” under "Related Downloads").


Table 1: Genome sizes and typical num­ber of samples per organism which can be sequenced in a single run on the Illumina NextSeq or MiSeq platform. Sample numbers are calculated to achieve >30x coverage per sample, taking into account pooling variabil­ity. In case of larger studies where two or more sequencing runs are required, it is possible to further optimize the sequencing resulting in even more samples per run.

Microsynth Competences and Services

With more than 7 years of experience in the field of next-generation sequencing, one of Microsynth’s core competences is to provide high quality one-stop servic­es. Re-sequencing of model organisms covers the entire process from experi­mental design planning, DNA isolation, Illumina sequencing up to a detailed bio­informatics analysis.


Experimental Design: Microsynth’s NGS specialists help you to define a suitable experimental set-up for your re-sequenc­ing project and discuss possible se­quencing strategies best suited to ad­dress your research question(s).

DNA Isolation: Either the customer pro­vides isolated DNA or outsources this step to Microsynth. Microsynth has a vast experience in DNA/RNA isolation from various and also demanding matrices like plant material, FFPE samples, etc.

Library Preparation and Sequencing: Following a quality check of your sam­ples, Microsynth will construct the Illu­mina library including specific sequenc­ing adaptors with barcodes. Depending on the experimental design, the libraries are pooled and sequenced either on the Illumina MiSeq or NextSeq platform. These flexible sequencing platforms al­lowing to optimize the sequencing strat­egy depending on the number of sam­ples/specimens.

Bioinformatics Analysis: Sequenced reads are quality-filtered and mapped against the reference genome of the or­ganism under study. Possible small inser­tions & deletions (small InDels) and sub­stitutions (SNPs) are detected based on the consense of three independent soft­ware packages. Beside useful summaries of sequencing and mapping, variant call­ing analyses are given in the VCF format. A variant calling step results in a user-friendly graphic summarizing the major findings of all investigated samples (e.g. specimens). For those variants which oc­cur within protein coding regions, the af­fected gene will be annotated and the impact on the translated amino acid se­quence is shown. As a consequence, each mutation detected can be specified (si­lent vs. missense vs. nonsense mutation). Structural variations are analyzed using the GASVPro package which searches for discrepancies between the observed and expected alignments of the paired-end sequencing data. Copy-number variation is either analyzed de-novo based on read-depth or against a reference speci­men sequenced in the study. Beside the raw data of the sequencing and the out­put of the analysis, a user-friendly sum­mary report is provided.

Examples for Most Important Output Files Provided by Microsynth

Figure 1: Typical output overview file (HTML) resulting from the variant calling step for SNPs and small InDels. For each sample and chromosome/contig the SNP and small Indels are reported separately and the effect of SNPs and small InDels for all annotated features of the reference genome are shown. SNPs and small InDels that are not located in a coding region are included and depicted as NA in the feature descriptions. Besides the html format the data are also given in the vcf format. In case that you sequence several samples/specimens a customized summary table including the different samples/specimens can be compiled according to your specifications.

Figure 2: Typical output of the analysis for structural variants given for each samples/specimens included in a study using GASVpro software. The location of the structural variation is given (leftChr and rightChr) and the approximate breaking point on the chromosome(s) are indicated by the boundary points (interval of coordinates to estimate the left and right break point) and the number of paired-end reads supporting the structural variation are given (Num PRS). The type of the structural varaition is indicated following the GASVpro definition (D = Deletion, IR = Reciprocal Inver­sion, I+/I- = Inversion, TR = Reciprocal Translocation, TN = Non-Reciprocal Translocation).

Figure 3: Example results of the analyses for copy-number variations. The copy-number variation can either be analyzed de-novo based on read-depth (see figure left) or against a reference included in the study (see figure right).

Further Readings
  • Langmead B, Salzberg SL: Fast gapped-read alignment with Bowtie 2. Nat Meth, 9(4): 357-359.
  • Wei Z, Wang W, Hu P, Lyon GJ, Hakonarson H: SNVer: a statistical tool for variant calling in analysis of pooled or individual next-generation sequencing data. Nucleic Acids Research, 39(19): e132.
  • Sindi S, Helman E, Bashir A, Raphael B: A geometric approach for classification and comparison of structural variants. Bioinformatics 2009, 25: i222-230.
  • Abyzov A, Urban AE, Snyder M, Gerstein M: CNVnator: An approach to discover, genotype, and characterize typical and atypical CNVs from family and population genome sequencing. Genome Research, 21(6): 974-984.
  • Xie C, Tammi M: CNV-seq, a new method to detect copy number variation using high-throughput sequencing. BMC Bioinformatics 2009, 10(1): 80.
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