Best Practices for Clinical Whole Genome Sequencing

Whole Genome Sequencing (WGS) is a powerful technique that allows scientists to analyze the complete DNA sequence of an organism, offering a comprehensive view of an individual's genetic makeup. It provides a more detailed picture of variations compared to targeted sequencing, enabling the detection of a wide range of genetic alterations like SNVs, insertions, deletions, mitochondrial variants.

WGS goes beyond just looking at genes, it also analyzes non-coding regions (introns, intergenic regions) which may play important roles in regulating gene expression and disease development.

WGS allows the detection of a broader range of variants, including small insertions and deletions, mitochondrial variants, repeat expansions, copy number variants, and other structural variants.

WGS can be used to diagnose a wide range of genetic disorders, including rare and complex conditions, by identifying disease-causing mutations.

WGs provides a comprehensive overview of an individual's genetic makeup, allowing for personalized medicine approaches.

The Medical Genome Initiative (MGI) has formed a working group to establish best practice recommendations for interpreting WGS data for clinical diagnostics.

MGI's working group is focusing on areas like data annotation, analysis, variant curation, reporting, and reanalysis to improve the accuracy and accessibility of WGS for clinical use.

Addressing the challenges and establishing best practices for WGS data interpretation are essential for increasing its adoption in routine clinical practice.

Variations in a single nucleotide that are the most common type of genetic change. These variations are often reviewed for their potential impact on health.

A process of selecting and analyzing genetic variations based on the patient's symptoms or family history.

A process of selecting and analyzing genetic variations based on known genetic associations or databases.

Variants that occur at the same position in the genome but have different alternate alleles. This means a single position can have multiple potential variations.

A type of genetic variation that affects the splicing process, which is important for creating functional proteins from DNA.

Genetic variations that have a high frequency in the population.

Resources that gather information and standards for interpreting genetic variations.

Variations that are less likely to cause significant health effects, but may still play a role in individual health. These variations may be associated with increased risk of certain diseases.

A type of analysis focusing on genetic changes linked to known diseases, including previously reported variants and predicted loss of function variants.

A special type of variant that disrupts a gene's function by altering the protein it codes for.

A gene analysis method that looks for new disease genes in individuals with specific symptoms, even if those genes haven't been linked to the disease before.

A database containing information about genetic variations and their link to diseases.

A database that catalogs the frequency of different genetic variants within populations.

An analysis that uses information about a patient's health condition or symptoms to guide the search for potential genetic explanations.

A process where labs carefully consider reporting genetic findings that might be related to disease but haven't been firmly established, based on the best available evidence.

A genetic variant that is present in only one copy of a gene.

A genetic variation where a segment of DNA is duplicated or deleted, potentially leading to changes in gene expression or function.

A process of checking all identified genetic changes for potential health impact, using both genetic and clinical information.

A process where genetic data is automatically compared with newly published scientific information to identify potential updates and revisions.

A process of carefully analyzing and reviewing the results of genetic testing by a trained expert to ensure accuracy and reliability.

A formal decision-making process to determine which genetic findings are considered significant and should be reported to patients and healthcare providers.

The ability of a genetic variant to cause a health condition, considering its impact on gene function and the likelihood of disease development.

Sharing information about genetic test results and their potential implications with both patients and their healthcare providers.

The process of reviewing previously analyzed genetic data from whole genome sequencing (WGS) for newly published genetic information and updated databases. This allows for a more comprehensive understanding of individual genetic variations and their potential impact on health.

The practice of considering a minimum time period (e.g., one year) to pass between the initial analysis of WGS data and a subsequent reanalysis. This ensures that enough new information is generated to warrant a review.

The use of information from multiple family members, such as a trio (parents and child), to identify genetic variants that are specific to a particular individual.

Detailed information about an individual's physical traits, medical history, and other relevant factors that can be used to interpret genetic findings.

Policies and procedures that clarify how laboratories will handle incidental findings, which are genetic variations that are not related to the primary reason for the genetic test but could have clinical significance.

Informed consent forms that clearly outline the uses of phenotypic information.

A type of genetic variation that involves changes in the number of copies of a DNA segment. This can affect gene dosage and lead to genetic disorders.

A laboratory technique used to analyze the complete DNA sequence of an organism. It provides a comprehensive view of an individual's genetic makeup.

A software tool that allows healthcare professionals to gather and analyze patient information, including medical history, symptoms, and physical characteristics.