A Guide to Using ClinTAD for Interpretation of DNA Copy Number Variants in the Context of Topologically Associated Domains

Curr Protoc Hum Genet. 2020 Dec;108(1):e106. doi: 10.1002/cphg.106.

Abstract

DNA copy number variants (CNVs) are routinely evaluated as part of clinical diagnosis in both the prenatal and postnatal genetic settings. Current guidelines for interpreting the potential clinical significance of these CNVs, typically identified by chromosomal microarray, focus entirely on genes localized within the CNV region. However, recent work has suggested that some CNVs can actually produce clinical impacts by influencing transcription of genes outside the CNV region. These alterations of transcription appear to occur by disrupting the composition of DNA topologically associated domains (TADs), which strongly influence contacts between gene promoters and their associated enhancers. Here we present a set of detailed protocols for the use of the free software tool ClinTAD (https://www.clintad.com). This decision-support software allows for prediction as to whether a given CNV may potentially disrupt a TAD boundary, and offers phenotype matching to genes near, but not within the CNV region, whose expression could be influenced by altered TAD architecture and that have phenotypic impacts related to that reported in a given patient. Our protocols here provide specific examples of how to implement these tools. In addition, the software has the capability to impact genomic research by evaluating multiple cases in parallel. We propose that this decision-support tool can benefit and improve genetic diagnosis. © 2020 Wiley Periodicals LLC. Basic Protocol 1: Evaluating a single case using ClinTAD Basic Protocol 2: Evaluating a single case with multiple variants using ClinTAD Basic Protocol 3: Evaluating multiple cases using ClinTAD Basic Protocol 4: Creating tracks with custom data.

Keywords: chromatin; decision support; genetics; microarray; topologically associated domains.

MeSH terms

  • DNA Copy Number Variations / genetics*
  • Databases, Genetic*
  • Genomics / methods*
  • Humans
  • Internet
  • Phenotype
  • Polymorphism, Single Nucleotide*
  • Software*
  • User-Computer Interface