Variant annotation (Nirvana Engine)
* requires control sample
High-resolution base-by-base view of the entire genome
Breadth of results
Identification of SNVs, Indels, SVs, CNVs and repeat expansion with a singel assay
Broad overview to assess genome-wide molecular alterations for further follow-on studies
New regulatory mechanisms
Identifies genome-wide potential disease-associated variants that might reveal new regulatory mechanisms
Fast turn-around-times for a comprehensive assessment and characterization of basically any genome
Whole exome sequencing (WES)
Unlike whole genome sequencing (WGS), whole exome sequencing (WES) focuses on the protein-coding region of the genome, which is called the exome. A person's exome accounts for just 1% (approx.) of the genome, which is why only approx. 30 million base pairs are read during WGS.
The human exome panel consists of 429,826 individual probes, spanning a target region of 39 Mb (19,396 genes) and covering 51 Mb of end-to-end tiled probe space.
Variant calling: somatic (Pisces) or germline (Starling) (VCF file)
Variant annotation (Nirvana Engine) or manual interpretation for a given set of genes
Identifies variants across a wide range of applications
Achieves comprehensive coverage of coding regions
Provides a cost-effective alternative to whole-genome sequencing (4-5 GB of sequencing per exome compared to ~90Gb per whole human genome)
Produces a smaller, more manageable data set for faster, easier analysis compared to whole-genome approaches
Whole transcriptome sequencing (WTS)
RNA sequencing (RNA-seq) analyzes the transcriptome; i.e. it is a quantitative determination of the transcribed (from DNA to RNA) genes present in the cell.
The expression of the transcriptome provides the basis for the identity of a cell and the associated functionality. Total RNA-Seq analyzes both coding and multiple forms of noncoding RNA for a comprehensive view of the transcriptome.
We also offer custom panels (xGen Lockdown Panels) in cooperation with IDT Integrated DNA Technologies. We offer sequencing of tailored panels from a sample number of 96. After indication of the target regions (chromosomal coordinates) a preparation time of 4-6 weeks is required (panel design, production and wet lab validation at MLL Dx).
Human ID Panel (MLL)
The human ID panel contains 24 SNPs that enable the unique identification of individual samples. Every panel designed at the MLL contains automatically the human ID panel.
Copy number variation (CNV) Panel
The CNV panel consists of 9115 individual probes spaced approximately every 0.34 Mb across the human genome.
If the available panels do not contain all the desired genes, it is also possible to mix the probes of individual genes to a panel in order to cover all desired regions. After indication of the additional target regions (chromosomal coordinates) a preparation time of 4 weeks is required (probe design, production and wet lab validation at MLL Dx).
A key step of any NGS library preparation is the addition of unique barcode sequences (= indexing) per sample that allow multiple libraries to be pooled and sequenced together. After the sequencing the index information is used to unequivocally assign the sequenced fragments (= reads) to the individual patients, automatically (bcl2fastq software) generating patient-specific FASTQ files. Converting raw sequencing data of a multiplexed run into sample-specific FASTQ files is called ‘demultiplexing’. In order to account for the known phenomenon of index hopping (=incorrect assignment of libraries from the expected index to a divergent index) it is recommended to use unique dual indexing pooling combinations to eliminate hopped reads from downstream analysis.
The FASTQ files are the input for the subsequent read alignment to the reference genome or, in the case of WTS, the reads can also be matched to their position on the reference transcriptome. The assembly of the human reference genome has evolved over time and for backward compatibility we align against GRCh37/hg19. The alignment process assigns each sequenced DNA fragment to its matching region in the human genome based on its base sequence. The position of the reads is stored as a sequence alignment/map (SAM) or binary alignment/map (BAM) file. Read alignment is a complex and computationally very intensive part of the pre-processing workflow that can be significantly accelerated by parallelisation. Hence, like most of the pre-processing steps, the alignment is performed in our private AWS instance of Amazon Cloud in Frankfurt (AWS, Amazon Web Services). DNA sequencing data (WGS, WES, gene panels) is aligned with the Isaac Aligner and for WTS data the STAR aligner is used.
The alignment result is used to identify deviating positions (=variants) from the reference genome, producing a list of variant calls detailed in a variant call format (VCF) file. Individual base exchanges (SNV, Single Nucleotide Variant), as well as smaller insertions and deletions can be detected. For larger assays such as WGS or WES it is necessary to rely on matched tumour-normal variant calling (Strelka2) to reduce false positive variant calls and to reliably distinguish somatic variants from germline variant calls. The sensitivity of WGS with ~100x coverage is about 10-15% mutation load. For WES with a ~250x coverage a sensitivity of 10% is reached. A tumor-only workflow (Pisces) is applied for gene panels but a specific post-screening of germline material might still be necessary to validate potential somatic variants. Gene panels are routinely sequenced with a target coverage of 1500x, allowing a sensitivity of >2% mutation load. Large deletions and medium-sized insertions, as they are for example found in CALR and FLT3, are called with Pindel. For WGS the copy number variants (CNV) as well as structural variants (SV) can be assessed. CNVs are called with CANVAS and SV with Manta. Fusion calling for WTS data is performed with Arriba, Manta and STAR-Fusion. Additionally Isaac Variant caller is used for SNV and small indel detection. For fusion detection paired-end reads are required.
To perform differential expression analysis to reference genes DESeq2 is used. For this approach control samples are needed as reference.
In order to facilitate the interpretation of identified variants, additional information about the detected variants can be provided. This includes the identification of the gene that overlaps with the variant, a precise characterization of the genomic region (exon, intron, intron-exon transition) in which the variant was found, a translation of the variant into a standardized nomenclature, an estimation of the possible functional effect of the found variant (missense, synonymous, polymorphism, etc.), and, for example, the population frequency as reported by gnomAD. The MLL routinely documents the evaluation of discovered sequence variants and, hence, in addition to clinical databases the in-house database can be assessed to estimate the clinical relevance for a multitude of variants. The annotation of vcf files can be done either automatized - based on public data bases only, using Nirvana engine and the following sources: VEP, ClinVar, COSMIC, dbSNP, gnomAD, DGV - or manually, using the MLL routine diagnostics workflow with variant classification for a defined set of genes.
Sequencing data is often sensible data that has to be protected by the highest security standards. Raw sequencing data from the NovaSeq system is directly streamed into a private AWS instance of Amazon Cloud in Frankfurt (AWS, Amazon Web Services), to which only selected employees at MLL have access. The data is completely anonymized with an arbitrary internal identifier and no personal or clinical data is stored in the cloud. The data security measures comply with the highest standards of the new EU General Data Protection Regulation (GDPR), which has also been verified by external auditors in their reports, including ISO 27001, ISO 27017 and ISO 27018. Furthermore, AWS has also been awarded the C5 attestation of the Federal Office of Information Security. Raw sequencing data from the MiSeq systems is stored locally without external access.
Please select a process on the left to learn more...
There are two fundamentally different approaches for library preparation for WGS: PCR-free and DNA amplification.
For the PCR-free method, a relatively large amount of input DNA is required (1ug), but it avoids PCR artifacts. Generally, sufficient DNA for a PCR-free library prep can be obtained from bone marrow and peripheral blood.
If the raw material exists in the form of fixed tissue (formalin-fixed, paraffin-embedded; FFPE) or as cell-free DNA from liquid biopsy samples, a pre-amplification method must be chosen in order to obtain sufficient material for the sequencing. Library prep includes the fragmentation of the DNA, end repair, and adapter ligation, which contain unique indexes such that each individual read after the sequencing can be uniquely identified as belonging to a patient. At MLL, library prep is performed in a fully automated procedure by pipette robots (Hamilton NGS Star). This ensures standardized and homogeneous library prep.
In addition to the fragmentation of the DNA, end repair, and adapter ligation, which contain unique indexes such that each individual read after the sequencing can be uniquely identified as belonging to a patient, library preparation for WES/PanelSeq also involves the enrichment of the coding sequences. Using probes, which exhibit a sequence complementary to the region of interest (panel of genes or the complete coding regions, exome) can be specifically selected (capturing) and enriched. There are two types of DNA fragmentation, enzymatic and mechanical fragmentation. While the TruSeq Library Prep (Illumina) uses mechanical fragmentation, Nextera Flex (Illumina) uses a enzymatic based fragmentation. At MLL, library prep is performed in a fully automated procedure by pipette robots (Hamilton NGS Star). This ensures standardized and homogeneous library prep.
As with the analysis of DNA (WGS, WES/PanelSeq), library preparation is conducted prior to the sequencing of the transcriptome. This process includes the fragmentation of the RNA, the removal of ribosomal RNA, the synthesis of cDNA from the RNA, the ligation of uniquely identifiable indices that make it possible to tell one sample apart from another, and a subsequent enrichment of the material via PCR.
At MLL, library prep is performed in a fully automated procedure by pipette robots (Hamilton NGS Star). This ensures standardized and homogeneous library prep.
Please select a method on the left to learn more...
At MLL Dx, sequencing is performed using the Illumina sequencing by synthesis method on the latest generation of sequencing devices, the NovaSeq 6000 or the MiSeq system. For already sequencing-ready libraries or pools a targeted output can be assessed by either a complete flow cell or lane of a flow cell, by the targeted clusters or reads [Mio], or by a given gigabase (Gb) output. The respective sequencing device is chosen based on the target read number/cluster passed filter or the target output [Gb], the used assay (influencing duplication and on-target rate) and the specifications given by Illumina for the respective system and flow cell.
While a coverage (depth) of 30x is often sufficient in human genetics, the detection of somatic mutations, and hence small clones as well, is of great importance in tumor biology. Therefore, sequencing is usually performed with a coverage of 60-90x for the tumor material, while sequencing of the normal controls is performed with 30x coverage.
Generally, a coverage (depth) of >100x is striven for during WES, as the detection of somatic mutations, and hence small clones as well, is of great importance in tumor biology.
In order to detect even small tumor clones, the PanelSeq aims for a high coverage (depth). The coverage usually exceeds 1,500x, with a minimum coverage of 400x to achieve a detection limit of 3%.
In order to achieve sufficient accuracy during the transcriptome analysis, the target is 50 million reads (sequenced fragments) per sample.
Usually, a "tumor-normal comparison" is performed in large scale genomic sequencing assays. By sequencing the tumor and e.g. peripheral blood as a normal control, the genome of a person can be compared for both materials, thereby allowing the differences in the tumor to be identified and benign polymorphisms to be eliminated.
In hematology, this is where we are faced with a huge challenge, as the frequently-used peripheral blood from patients with hematological neoplasia already contains the "tumor," namely the leukemia cells, which means that it is not an option for an easily available normal control. For this reason, buccal swap or fingernails are usually used in the field of hematology. However, it can be challenging to isolate sufficient DNA for sequencing from these materials. Alternatively, sorted T cells of the patient might be an option.
If no normal material is available, you will have to find other solutions. Hence, we use a "tumor-unmatched normal" workflow in order to eliminate artifacts and a percentage of the polymorphisms. This involves utilizing sequences of healthy controls from other persons.
Microscopic basic diagnostic for hematological, systemic diseases and staging of lymphoma.
Cellularity and different distribution patterns can usually be assessed after careful study of the entire specimen using lower magnification. This is followed by an individual analysis of at least 100 cells from the peripheral blood and at least 200 cells from two representative areas of the bone marrow. More important than simply counting the cells is its study by an experienced investigator based on the criteria of cell density, the ratio of erythropoiesis to granulopoiesis, distribution according to various maturity stages (in particular the % of blasts), changes in the cytoplasm and nucleus, the eosinophil, basophil and monocyte count, megakaryocytes (quantitative and qualitative), as well as the distribution and fine structure of lymphocytes, plasma cells and reticulum cells. Moreover, the assessment also includes iron staining and cytochemical reactions (peroxidase and non-specific esterase) for the determination of blasts.
Identification and characterization of chromosome aberrations of prognostic relevance by means of chromosome banding analysis.
Determining the karyotype is based on chromosome banding analysis. This requires a sufficient number of metaphases in good quality. The bone marrow or blood cells are cultivated for 24 to 72 hours dependent on the cell type and then arrested at the metaphase stage by adding colcemid. Cytokines can be added to stimulate the malignant cell population and increase the metaphase yield during cultivation. Swelling of the cells is induced by adding a hypotonic potassium chloride solution; they are then fixed in this state by a methanol/glacial acetic acid solution. The cell suspension is then dripped onto the slide. It is mandatory to conduct chromosome banding in order to ensure an unequivocal identification of the individual chromosomes. The most frequently used techniques are G- (giemsa), Q- (quinacrine) and R- (reverse) banding. The various banding techniques produce light and dark bands on the chromosomes that are specific to each one and that hence permit unequivocal identification of the individual chromosomes. According to international consensus, 20–25 metaphases should be fully analyzed in order to produce a reliable diagnosis (ISCN).
Fluorescence in situ hybridization (FISH): Use of fluorescence probes for the identification of aberrant chromosome in metaphases and distinct genetic abnormalities in interphase nuclei.
The FISH technique is based on the hybridization of DNA probes that identify specific chromosomal structures. It is possible to use probes that mark specific centromere regions of individual chromosomes, genes or entire chromosomes. The DNA of the selected probes and the patient DNA requiring analysis are denatured, meaning that the two DNA strands of the double helix are separated. During subsequent renaturation, the DNA probes accumulate on the complementary sections of the patient DNA (hybridization). The DNA probes directly carry the fluorescent marker. Therefore, the matching chromosome structures show up as fluorescence signals
Characterization and quantification of benign and malignant cell populations in peripheral blood or bone marrow and determination of minimal residual disease (MRD).
Characterization involves multi-parametric flow cytometry (MFC) of the analyzed cell populations. This procedure uses fluorescence dye-conjugated monoclonal antibodies targeting diagnostically relevant antigens on the cell membrane and in the cytoplasm. Modern flow cytometers enable simultaneous detection of several different fluorochromes and hence allow a precise description of antigen expression patterns for approximately 1,000 cells per second. This means that even cell populations at a frequency of 1% or less can be characterized very quickly.
State-of-the-art methods for the identification of gene mutations with the highest sensitivity; preparation of genetic tumor profiles and determination of minimal residual disease (MRD).
Molecular genetics combines a variety of different methods using either genomic DNA or cellular RNA (reverse transcribed into cDNA) as template. The spectrum of analyses ranges from the isolation of white blood cells and extraction of nucleic acids as sample preparation to PCR, quantitative PCR, digital PCR, Next generation sequencing (NGS), fragment length analysis, clonality detection and chimerism. Each of these methods comprises a variety of specific assays. Through panel diagnostics, a broad portfolio of gene mutations can be examined in parallel using a single approach, whereas highly sensitive methods such as quantitative PCR achieve detection limits of 10-5.
Rapid diagnostics enables rapid initiation of therapies. We understand, that it is critical to wait for a result, especially for the patient. Therefore, we try to perform the analyses in the shortest possible time without loosing our quality standards. Average time from sample receipt to reporting:
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All samples are processed according to the international standards DIN EN ISO 15189 "Medical
laboratories - special requirements for quality and competence" and DIN EN ISO/IEC 17025 "General
requirements for the competence of testing and calibration laboratories" .
Accuracy of results cannot be guaranteed. The manner in which the services generate results,
other information is complex, dependent upon operator accuracy, pre- and post-analytical factors,
the possibility of software or other error cannot be eliminated.