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1.1.1 Overview

Genetic reporting involves reporting information about the genetic characteristics of a sample. The sample might be a tissue sample from a human, an animal or, more rarely, a bacteria or virus. In humans and animals, the sample might be from "normal" tissue, transplanted tissue, reproductive tissue (egg or sperm) or abnormal tissue such as a tumor.

Reporting is typically done on the specimen's DNA (chromosomal or occasionally mitochondrial DNA), however it can also be done on RNA and proteins (amino acid sequences).

Because DNA, RNA and even amino acid sequences can be exceptionally long - and are typically mostly the same for a given type of organism or protein - reporting is typically done on the basis of variations between the tested specimen and a reference specimen rather than as a complete enumeration of the whole sequence. This approach is also used because clinical relevance of genetic tests is based on the presence of diverges from the norm. Note that a sequence might still be relevant (and might still be referred to as a variation) even if it is unchanged from the reference.

Differences in sequences (variations) are are detected (and documented) using a variety of different techniques each of which has trade-offs in terms of applicability (some can only be used for DNA but not RNA or amino acid sequences or can only detect certain types of changes), cost, speed, availability and precision. A genetic report may contain information gathered from multiple testing approaches. For example, a more general test might be followed up with more specific tests providing additional details.

Variations can be described at different levels of granularity ranging from chromosomal or poly-chromosomal abnormalities such as extra or missing chromosomes or large-scale differences (e.g. fragile X) down to single changes in individual nucleotides (Single Nucleotide Polymorphisms or SNPs). Intermediate levels may group multiple changes together. Such groupings can be based on a number of considerations:

• The technique used to detect the variation
• Alignment with the borders of major features of the underlying sequence (e.g. gene variants)
• The presumed cause of the difference (insertion of extra copies, inversion of a portion of the sequence
• Common patterns in the population (a common set of variations typically appear together)
• A known effect (a particular collection of changes may result in a known physical manifestation or disease - aka. a phenotype)

Groupings may themselves be organized into higher-level groupings based on the same criteria.

"Known" variations are often assigned codes and catalogued into terminologies. This allows easy linking of knowledge to information found in a particular specimen. Reports can simply specify the code and know that clinicians can look up relevant information associated with the code. However, sometimes variations are detected that do not (yet) have a standardized code. In these cases, a description of the variation and where it was located must be communicated. Often, even when a code is known, the details about the location and type of change are communicated

1.1.2 Key Reporting Elements

The focal element for genetic reporting is the DiagnosticReport resource. It summarizes and packages all of the information found, organizes it for consumption and provides a summary as well as a rendered view of the findings. It is the primary response to the ServiceRequest which is the "order" for genetic testing to occur. In practice, there can be multiple ServiceRequests grouped together as part of a single requisition. This allows multiple tests to be ordered at one time and the results to be gathered as a group. The organization of the report is accomplished by subsetting data into panels (and sometimes sub-panels). The structure of these panels is usually driven by the types of testing requested, though they can vary depending on the reporting lab. In some cases, no panel organization will be provided at all.

As part of a report of genetics key components to enumerate are: findings, interpretation, impact and recommendations. Findings in genetics are a specific report of the divergences from the norm. For example, a patient sample may have a DNA sequence difference from a reference sequence. The finding is the sequence present in the patient, which can only be understood in the context of a reference Sequence used to indicate the norm. Or, a patient sample has a chromosomal aberration (such as duplication of a chromosome), where the reference is considered to be a generic arrangement of chromosomes. Another example is the microarray detected presence of a SNP, here the reference is the probe set sequence used for detection. Commonly, these findings are reported with interpretations, impacts and recommendations. Interpretations are high-level statements that indicate that a divergence was found. Such as a statement that the sample is 'positive for CYP2C19*1.' Impacts provide an elaboration of the effect of the interpretation, such as ‘poor response to medication.' For the reported impacts, recommended actions may be included, such as 'reduce dosage.'

1.1.3 Variant Reporting

DNA, RNA and amino acid sequences can all be examined through a variety of mechanisms. These range from direct sequencing, inference from microarrays, and mass spectrometry. Additionally, DNA differences are sometimes reported on the basis of cytogenetic analysis - visually examining one or more chromosomes using high-powered magnification and various staining techniques to identify discrepancies

Sequence is a term that indicates a connected series of joined base molecules - a polymer of subunits. For DNA and RNA the bases (or monomeric subunits) are nucleotides. For proteins the bases are amino acids. In the cell, the polymers that comprise DNA or RNA or proteins exist in many discrete molecules. DNA polymers are further organized into structures called chromosomes.

Direct sequencing techniques follow a multistep pathway. The initial phase of a sequencing run produces raw sequence with a qualification of the quality of the raw sequence. The raw sequence is then subject to further computational analysis. In traditional sequencing the product is a single 'read' and the initial step is often the final step. However, in techniques such as next-generation sequencing, the initial step is massively parallel and many 'reads' result. The next phase for massively parallel sequencing techniques is to align the 'reads' to each other and a reference sequence, which acts as a scaffold to aid in assembling 'reads,' in order to create longer, contiguous series of sequences. The next phase for traditional and highly-parallel sequencing techniques is to compare the sequence, or sequence of the assembled 'reads,' to a reference sequence. This comparison produces indientification of variance and quality scores.

Inferential techniques for determining variants in sequences rely upon a standard as a reference. For example, inference from microarrays is done through comparing the signal produced by a sample to a known standard reference. In the case of microarrays, the probe set used conveys the positions interrogated. In Mass spectrometry, the standard is the mass of a known reference. In inferential techniques the output is the presence or absence of variation with a technique specific measurement of accuracy.