Gene Panel Design: ACMG Standards

The Paper

Bean et al. recently published a report “Diagnostic gene sequencing panels: from design to report – a technical standard of the American College of Medical Genetics and Genomics (ACMG)” that provides technical standards for the design of gene panels.  The report and standards will be of interest to clinical researchers and others who wish to create gene panels for diagnostics and gene-disease association.



In the interest of time, we’ll summarize the ACMG (American College of Medical Genetics and Genomics) standards and guidelines for gene panel design.  Consult the full paper for more in-depth discussions.


The ACMG defines a diagnostic gene panel as a stand-alone clinical assay for a specified clinical indication derived from a limited gene set.  Today, most gene panels are designed for short-read Next Generation Sequencing.


The ACMG differentiates two types of genes:

  • GAD (genes associated with Mendelian disorders).  These genes have definitive, strong or moderate supporting evidence in the scientific literature and clinical databases.  In most cases a full set of GAD genes should be included in gene panels.
  • GUS (genes of uncertain significance).  These genes have limited or disputed supporting evidence.  In most cases GUS genes should be excluded from gene panels.


The ACMG recommends that the gene sets included in gene panels demonstrate the following properties:

  • Sensitivity and Specificity. The sequencing results and identified variant alleles from a gene panel should match the clinical indications and disease phenotypes in a high proportion of cases. Thus, the GAD set must be carefully chosen for any specific disease state.
  • Validity.  Gene-disease associations should be corroborated with a curated source such as ClinGen.


There are a variety of clinically relevant databases that can be used to identify genes for inclusion in gene panels, including ClinVar, HGMD, Cosmic, OMIM, ClinGen, dbSNP and others.  And GQuery is an excellent tool for performing an integrated search across the NCBI database set.


Exclusion criteria are just as important as inclusion criteria.  In general, GUS genes will be excluded from gene panels.  However, if GUS genes are included in a panel, they should be clearly delineated from GAD genes in final reports, with attendant disclaimers that these genes have unproven gene-disease associations.


Technical Issues

For any NGS-based gene panel design, there will be technical considerations that affect the choice of genes or regions-of-interest (ROI) to include in a panel.

  • Genomic regions with high sequence homology can be difficult for sequence alignment algorithms.
  • Genomic regions with exceptionally high or low GC content can be difficult to sequence.
  • Homopolymer sequences can prohibit NGS sequencing or yield regions with low coverage.
  • Extensive repeat sequences can lead to regions of low coverage for specific genes, exons or other ROI’s.
  • Duplicated pseudogenes may display sequence homology across exonic and intronic regions, making it hard to design amplicons that map correctly to each pseudogene.
  • Alternative splicing can yield numerous mRNA transcripts for a given set of exons.
  • Copy-number variants derived from NGS results may need independent validation from other methods.



The ACMG recommends that researchers follow existing guidelines for NGS reports as specified in Rehm et al.  “ACMG clinical laboratory standards for next-generation sequencing”.  In addition, for gene panels they suggest including:

  • Clinical indications of the panel
  • Clinical sensitivity of the panel
  • Clinical specificity of the panel
  • List of genes in the panel
  • Scope of panel (i.e. broad comprehensive panel or narrow targeted subpanel)
  • Indicate if panel has consent requirements
  • If appropriate, identify specific transcripts expected from the panel
  • Identify expected gene-disease associations
  • If appropriate, identify expected inheritance patterns


The ACMG also includes a useful workflow model for designing, evaluating and implementing gene panels.  Their guidelines may be helpful for researchers venturing into panel design.


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