Evidence map›Paper›PMID 19222838›Full record

ArticleBMC genetics2009

Determining the effectiveness of High Resolution Melting analysis for SNP genotyping and mutation scanning at the TP53 locus.

Sonia Garritano, Federica Gemignani, Catherine Voegele, Tú Nguyen-Dumont, Florence Le Calvez-Kelm, Deepika De Silva, Fabienne Lesueur, Stefano Landi, Sean V Tavtigian

Open access · diamondAbstract readComparative Study
In one paragraph

Article in BMC genetics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
65citing papers in PubMed, 2 pooled it
4.8field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

65 citing papers in PubMed, 2 syntheses or guidelines pooled it, 147 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Genetic analysis ofArchives animal breeding · 2025
    Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Generation and Characterization of a Zebrafish IL-2Rγc SCID Model.International journal of molecular sciences · 2022
    Article
  16. Article
  17. Article
  18. B cell lymphoma 6A regulates immune development and function in zebrafish.Frontiers in cellular and infection microbiology · 2022
    Article
  19. Article
  20. Article

5 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 2 institutions in 2 countries.

Sonia GarritanoDepartment of Biology, Genetics via Derna 1, University of Pisa, Pisa, Italy. garritanos@iarc.fr
Federica Gemignani
Catherine Voegele
Tú Nguyen-Dumont
Florence Le Calvez-Kelm
Deepika De Silva
Fabienne Lesueur
Stefano Landi
Sean V Tavtigian
Centre International de Recherche sur le Cancer · FRUniversity of Pisa · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTogether single nucleotide substitutions and small insertion/deletion variants are the most common form of sequence variation in the human gene pool.High-resolution SNP profile and/or haplotype analyses enable the identification of modest-risk susceptibility genes to common diseases, genes that may modulate responses to pharmaceutical agents, and SNPs that can affect either their expression or function. In addition, sensitive techniques for germline or somatic mutation detection are important tools for characterizing sequence variations in genes responsible for tumor predisposition. Cost-effective methods are highly desirable. Many of the recently developed high-throughput technologies are geared toward industrial scale genetic studies and arguably do not provide useful solutions for small laboratory investigator-initiated projects. Recently, the use of new fluorescent dyes allowed the high-resolution analysis of DNA melting curves (HRM).

resultsHere, we compared the capacity of HRM, applicable to both genotyping and mutation scanning, to detect genetic variations in the tumor suppressor gene TP53 with that of mutation screening by full resequencing. We also assessed the performance of a variety of available HRM-based genotyping assays by genotyping 30 TP53 SNPs. We describe a series of solutions to handle the difficulties that may arise in large-scale application of HRM to mutation screening and genotyping at the TP53 locus. In particular, we developed specific HRM assays that render possible genotyping of 2 or more, sometimes closely spaced, polymorphisms within the same amplicon. We also show that simultaneous genotyping of 2 SNPs from 2 different amplicons using a multiplex PCR reaction is feasible; the data can be analyzed in a single HRM run, potentially improving the efficiency of HRM genotyping workflows.

conclusionThe HRM technique showed high sensitivity and specificity (1.0, and 0.8, respectively, for amplicons of <400 bp) for mutation screening and provided useful genotyping assays as assessed by comparing the results with those obtained with Sanger sequencing. Thus, HRM is particularly suitable for either performing mutation scanning of a large number of samples, even in the situation where the amplicon(s) of interest harbor a common variant that may disturb the analysis, or in a context where gathering common SNP genotypes is of interest.

Indexed as

GenotypePolymorphism, Single NucleotideCell Line, TumorDNA Mutational AnalysisDNA, NeoplasmHomozygoteHumansNucleic Acid DenaturationSensitivity and SpecificityTumor Suppressor Protein p53DNA, NeoplasmTP53 protein, humanTumor Suppressor Protein p53

Identifiers

PMID19222838
PMCPMC2648999
OpenAlexW2033212459

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.