Evidence map›Paper›PMID 28548214›Full record

ArticleJournal of clinical laboratory analysis2018

The performance of MALBAC and MDA methods in the identification of concurrent mutations and aneuploidy screening to diagnose beta-thalassaemia disorders at the single- and multiple-cell levels.

WeiQiang Liu, HuiMin Zhang, Dan Hu, SiJia Lu, XiaoFang Sun

Open access · bronzeAbstract read
In one paragraph

Article in Journal of clinical laboratory analysis, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
4.9field-weighted citation impact, top 6% 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

20 citing papers in PubMed, 29 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
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  6. Review
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  9. Article
  10. Advances in Genetic Diagnosis of Kallmann Syndrome and Genetic Interruption.Reproductive sciences (Thousand Oaks, Calif.) · 2022
    Review
  11. Review
  12. Review
  13. Article
  14. ART strategies in Klinefelter syndrome.Journal of assisted reproduction and genetics · 2020
    Review
  15. Article
  16. Article
  17. Haploseek: a 24-hour all-in-one method for preimplantation genetic diagnosis (PGD) of monogenic disease and aneuploidy.Genetics in medicine : official journal of the American College of Medical Genetics · 2019
    Article
  18. [Rapid preimplantation genetic diagnosis ofNan fang yi ke da xue xue bao = Journal of Southern Medical University · 2018
    Article
  19. Article
  20. Article
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

5 authors at 2 institutions in 1 country.

WeiQiang LiuKey Laboratory for Major Obstetric Diseases of Guangdong Province, Key Laboratory for Reproduction and Genetics of Guangdong Higher Education Institutes, Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
HuiMin ZhangKey Laboratory for Major Obstetric Diseases of Guangdong Province, Key Laboratory for Reproduction and Genetics of Guangdong Higher Education Institutes, Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Dan HuKey Laboratory for Major Obstetric Diseases of Guangdong Province, Key Laboratory for Reproduction and Genetics of Guangdong Higher Education Institutes, Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
SiJia LuYikon Genomics Co. Ltd., Jiangsu, China.
XiaoFang SunKey Laboratory for Major Obstetric Diseases of Guangdong Province, Key Laboratory for Reproduction and Genetics of Guangdong Higher Education Institutes, Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.ORCID http://orcid.org/0000-0002-3308-5325
Third Affiliated Hospital of Guangzhou Medical University · CNSinotech Genomics (China) · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo select an optimal whole-genome amplification (WGA) method to improve the efficiency of the preimplantation genetic diagnosis and screening (PGD/PGS) of beta-thalassaemia disorders.

methodsFifty-seven fibroblast samples with defined beta-thalassaemia variations and forty-eight single-blastomere samples were amplified from single-, two-, and five-cell samples by multiple annealing and looping-based amplification cycles (MALBAC) and the multiple displacement amplification (MDA) method. Low-depth, high-throughput sequencing was performed to evaluate and compare the coefficiencies of the chromosomal copy number variation (CNV) detection rate and the allele dropout (ADO) rate between these two methods.

resultsAt the single-cell level, the success rates of the CNV detection in the fibroblast samples were 100% in the MALBAC group and 91.67% in the MDA group; the coefficient of variation in the CNV detection in the MALBAC group was significantly superior to that in the MDA group (0.15 vs 0.37). The total ADO rate in the HBB allele detection was 4.55% in the MALBAC group, which was significantly lower than the 22.5% rate observed in the MDA group. However, when five or more cells were used as the starting template, the ADO rate significantly decreased, and these two methods did not differ significantly.

conclusionsFor the genetic diagnosis of HBB gene variation at the single-cell level, MALBAC is a more suitable method due to its higher level of uniformity and specificity. When five or more cells are used as the starting template, both methods exhibit similar efficiency, increased accuracy, and a similar success rate in PGD/PGS.

Indexed as

Aneuploidybeta-ThalassemiaDNA Mutational AnalysisFemaleHigh-Throughput Nucleotide SequencingHumansNucleic Acid Amplification TechniquesPregnancyPreimplantation Diagnosisbeta-thalassaemiamultiple annealing and looping-based amplification cyclesmultiple displacement amplificationwhole-genome amplification efficiency

Identifiers

PMID28548214
PMCPMC6817139
OpenAlexW2618189314

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Registered trials

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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.