Wet lab

Next generation sequencing (NGS) has been adopted in all areas of molecular diagnosis. Laboratories must become familiar with the critical differences between NGS and traditional Sanger sequencing. The wet laboratory process is one such area of critical difference. Robust quality assurance and quality control procedures are essential to ensuring the reliability of NGS testing results.

This chapter will focus on the “wet” laboratory issues including laboratory environment, sample/library preparation, template generation, sequencing and quality assurance in genomic diagnostic application.

Many of the guidelines in this document are common to all forms of nucleic acid testing. These guidelines should be read in conjunction with ISO 15189 and all relevant NPAAC documents, but particularly Requirements for Medical Testing of Human Nucleic Acids, and Requirements for the Development and Use of In-House In Vitro diagnostic Devices.

We propose that these principles and guidance could form a foundation for future specifications of performance and formal regulations of genomic testing. It is not our intention to generate a user guide and provide all the solutions. Instead, we try to include some relevant resources for your reference. For example, some relevant “wet” laboratory issues can be found from the website of the Division of Laboratory Programs, Standards, and Services (DLPSS) of the American Centers for Disease Control and Prevention (CDC).

1.1.1 Resources

Laboratories should ensure the physical design can accommodate separate areas for patient derived samples and amplified material.

Possible cross contamination between these areas including by movement of equipment, staff, or aerosols should be assessed and managed.

Measures should be available to both detect cross contamination between clinical samples, and to eliminate it. Detection may include the use of processing blanks or environmental monitoring. Elimination may include the use of hypochlorite or other decontamination measures.

For further information refer to refer to NPAAC Requirements for the Medical Testing of Human Nucleic Acids.

Laboratories should ensure recommended and appropriate maintenance and cleaning processes are performed to eliminate carryover contamination.

Laboratories should include a monitoring process for carryover contamination as part of regular internal quality control.

Sample indexes (barcodes) used to identify unique reads in pooled libraries can be used to detect carryover contamination. These should be re-used on the longest cycle possible. Consecutive runs of the same sequencing instrument using the same barcode indexes should be avoided. Frequent re-use of the same set of barcode indexes will compromise the laboratory's ability to detect cross-contamination at any stage of the sequencing procedure.

The laboratory should avoid workflows that offer the potential for undetectable sample cross-contamination. Workflows that call for multiple manipulations, additions, and incubations of samples prior to index ligation or amplification increase the risk of undetectable sample to sample cross-contamination whereas workflows which add unique indexes to each sample early in the library preparation process provide a means to make cross-contamination detectable.

Identity SNPs’ could be included within each assay and interrogated with a second method to confirm patient identity, if no unique variants are identified within the genes analysed. These SNPs can also be used to monitor and detect any carryover contamination within the data. Where members of the same pedigree have been analysed, bioinformatics analyses to confirm family relatedness may also prove useful to highlight errors in specimen identification, processing or contamination.

Consideration should be given to biases inherent in the platform of choice. Particular attention should be given to ensuring that any systematic weaknesses or errors of the sequencing system do not limit the diagnostic specificity of the assay, or that if such flaws exist, that orthogonal testing is employed to detect variants in regions of bias. Examples include regions of high GC content or repetitive regions.

Expansion of genomic methods for diagnostic applications makes it increasingly important to demonstrate data quality, reliability and reproducibility. Diagnostic laboratories should empirically determine their minimum requirements for data quality.

Analytic sensitivity and specificity are important performance characteristics for genomic diagnostic applications. Diagnostic laboratories should document these aspects of the laboratory workflow by comparison of test results obtained under conditions defined above, to those obtained from a gold standard method (usually Sanger sequencing).

3.2.1 Resources

Inclusion of known DNA control/standard samples at <10% of the pooled libraries at regular intervals would allow ongoing monitoring of assay performance and data analysis processes.

If part of the genomic testing process is to be outsourced, NATA accredited providers or providers showing full compliance with NPAAC standards must be used. It remains the responsibility of the clinical laboratory to review, retain and furnish for audit all documentation related to clinical testing.

Failure to exclude samples of poor quality or insufficient quantity of amplifiable DNA can significantly affect the sensitivity and specificity of genomic diagnosis and lead to the possibility of false negative results. This is of particular significance where the sample type may be associated with limiting amounts of DNA, for example FFPE tissue or cell-free circulating DNA. Failure of sample exclusion can also affect turnaround time, due to the long cycle of the genomic testing process.

In the case of measuring cell-free circulating DNA for the purposes of non-invasive prenatal screening or testing, the laboratory should have a process to ensure that adequate amounts of foetal DNA (i.e. in accordance with the sensitivity limit determined for the assay) are present in the sample prior to data analysis and interpretation of results.

Where appropriate, consideration should be given to including related affected and unaffected samples in the analysis. For example sequencing trios (proband and both parents) to confirm a de novo change, or tumour and normal samples to exclude a cancer variant as germline.

Assessment of tissue volume and cellularity is usually estimated by microscopic examination by a competent person. Sufficient purity or proportion of targeted cells can then be achieved through macro-dissection.

For laboratories handling in excess of 1000 samples per year, a Laboratory Information Management System capable of tracking a multistep workflow, with multiple samples, and QC steps should be considered.

For those laboratories that use protocols making use of DNA fragmentation, quality assessment of DNA fragmentation procedure is essential to ensure the right size distribution and accurate amount of fragmented DNA samples. The latter is critical for equal molar representation if multiple barcoded samples are to be subsequently pooled for library preparation.

The laboratory should determine the optimal conditions for library preparation. Documented metrics of performance of library preparation should be generated and used to QC library preparation steps on all clinical samples. For example, effect of input mass of DNA, fragmentation conditions, PCR cycles, etc. should be assessed. QC metrics in the form of Bioanalyser traces, spectrophotometric readings, or real-time PCR results should be produced and routinely collected and compared to those of an optimal validated run.

An accurate estimation of DNA library quantity is essential for optimal clonal amplification.

Quantification should be based on amplifiable templates (i.e. DNA fragments with proper ligated adaptors). For example, quantitative PCR (qPCR) has high levels of sensitivity and specificity and can accurately measure quantities of DNA.

Quality assessment of the clonal amplification procedure is essential to ensure an adequate representation of DNA samples in the template. This is critical for equal representation if multiple barcoded samples have been pooled during library preparation.

The laboratory should employ quality control measures that specify the quantity and quality of DNA sequence data to accurately differentiate all targeted sequence variants. This is especially critical when a multiplexed target enrichment procedure has been used to generate libraries

The laboratory should ensure that there is sufficient coverage for the detection of aneuploidy e.g. in non-invasive prenatal trisomy 21 testing.

Consideration should be given to the use of barcoded DNA samples and the possibility of sequence data being misdirected to the wrong specimen.

7.2.1 Resources

Consideration should be given what would be the suitable data format to keep (see further discussion in Bioinformatics Section). The raw reads and quality scores should be kept as a minimal requirement.

Data storage should also comply with overarching regulatory and legislative requirements (see section in Ethical & Legal Issues.)

This exception log should be kept with the reason(s) for deviation and should retain links to the patient sample.

7.4.1 Resources

Consideration should be given to cross platform confirmation. Sanger sequencing should be considered to reduce false positive and/or negative rates, particularly in small indel variants.

The limitation of genomic testing should be presented in the final report (See the details in the Reporting section).

QC of sequencing data may include:

  • Base call quality scores
  • Read depth
  • Uniformity of read coverage
  • Read enrichment (for capture-based methods)
  • Percentage PCR duplicates (for capture-based methods)
  • Allelic Read Percentage
  • GC bias
  • Decline in signal intensity along a read

Well-characterised DNA samples should be used as internal quality control samples. Cell lines are renewable, but may have some balanced or unbalanced chromosomal rearrangements. Blood samples from young subjects (<55 years) are typically free from such rearrangements, but have limited supply. Rearrangements that are identified may reflect the age of the donor or be a consequence of the culture process. Consideration should also be given to obtaining reference materials from overseas. For example, the Food and Drug Administration of the United States of American has recently completed the Sequencing Quality Control (SEQC) project, as a part of Phase III of the MicroArray Quality Control (MAQC-III) project. Its aims were to assess the technical performance of genomic platforms by generating benchmark datasets with reference samples, and to evaluate the advantages and limitations of various bioinformatics strategies in RNA and DNA analyses.

Acceptable intra-and inter-run variability should be established during validation and monitored in diagnostic laboratories. It is important to determine assay precision, i.e., the degree to which repeated measurements give the same result – both repeatability (within-run precision) and reproducibility (between-run precision).

Genomic technologies are rapidly evolving. Consideration should be given whether positive findings in genomic analysis should be confirmed by a different chemistry or a second method, particularly at the initial validation stage and for results that affect clinical decision-making.

The laboratory should monitor, implement and validate upgrades to instruments, sequencing chemistries and reagents or kit used to generate genomic data.

8.2.1 Resources

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