Accurate diagnosis of spinal muscular atrophy and 22q11.2 deletion syndrome using limited deoxynucleotide triphosphates and high-resolution melting

Accurate diagnosis of spinal muscular atrophy and 22q11.2 deletion syndrome using limited deoxynucleotide triphosphates and high-resolution melting

Zhang, Xiaoqing;Wang, Bo;Zhang, Lichen;You, Guoling;Palais, Robert A.;Zhou, Luming;Fu, Qihua;
BMC genomics 2018 Vol. 19 pp. 1-7
362
zhang2018accuratebmc

Abstract

Abstract Background Copy number variation (CNV) has been implicated in the genetics of multiple human diseases. Spinal muscular atrophy (SMA) and 22q11.2 deletion syndrome (22q11.2DS) are two of the most common diseases which are caused by DNA copy number variations. Genetic diagnostics for these conditions would be enhanced by more accurate and efficient methods to detect the relevant CNVs. Methods Competitive PCR with limited deoxynucleotide triphosphates (dNTPs) and high-resolution melting (HRM) analysis was used to detect 22q11.2DS, SMA and SMA carrier status. For SMA, we focused on the copy number of SMN1 gene. For 22q11.2DS, we analyzed CNV for 3 genes (CLTCL1, KLHL22, and PI4KA) which are located between different region-specific low copy repeats. CFTR was used as internal reference gene for all targets. Short PCR products with separated Tms were designed by uMelt software. Results One hundred three clinical patient samples were pretested for possible SMN1 CNV, including carrier status, using multiplex ligation-dependent probe amplification (MLPA) commercial kit as gold standard. Ninety-nine samples consisting of 56 wild-type and 43 22q11.2DS samples were analyzed for CLTCL1, KLHL22, and PI4KA CNV also using MLPA. These samples were blinded and re-analyzed for the same CNVs using the limited dNTPs PCR with HRM analysis and the results were completely consistent with MLPA. Conclusions Limited dNTPs PCR with HRM analysis is an accurate method for detecting SMN1 and 22q11.2 CNVs. This method can be used quickly, reliably, and economically in large population screening for these diseases.

Citation

ID: 20929
Ref Key: zhang2018accuratebmc
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
20929
Unique Identifier:
4c08390ed79e7e06de88777d341a844b
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet