Evidence map›Paper›PMID 32681760›Full record

ArticleHLA2020

Genomic characterization of MICA gene using multiple next generation sequencing platforms: A validation study.

Yizhou Zou, Jamie L Duke, Deborah Ferriola, Qizhi Luo, Jenna Wasserman, Timothy L Mosbruger, Weiguang Luo, Liang Cai, Kevin Zou, Nikolaos Tairis and 5 more

Open access · bronzeAbstract read
In one paragraph

Article in HLA, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.8field-weighted citation impact, top 29% 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

4 citing papers in PubMed, 10 citations in OpenAlex.

  1. Association ofZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2025
    Article
  2. Article
  3. Article
  4. 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

15 authors at 3 institutions in 2 countries.

Yizhou ZouDepartment of Immunology, Central South University Xiangya School of Medicine, Changsha, Hunan, China.ORCID 0000-0002-9261-1161
Jamie L DukeDepartment of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.ORCID 0000-0002-4768-0846
Deborah FerriolaDepartment of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Qizhi LuoDepartment of Immunology, Central South University Xiangya School of Medicine, Changsha, Hunan, China.
Jenna WassermanDepartment of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Timothy L MosbrugerDepartment of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Weiguang LuoDepartment of Immunology, Central South University Xiangya School of Medicine, Changsha, Hunan, China.
Liang CaiDepartment of Immunology, Central South University Xiangya School of Medicine, Changsha, Hunan, China.
Kevin ZouDepartment of Immunology, Central South University Xiangya School of Medicine, Changsha, Hunan, China.
Nikolaos TairisDepartment of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Georgios DamianosDepartment of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Ioanna PagkratiDepartment of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Debra KukurugaDepartment of Pathology, University of Maryland School of Medicine, Baltimore, Maryland, USA.
Yanping HuangDepartment of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Dimitri S MonosDepartment of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Children's Hospital of Philadelphia · USCentral South University · CNUniversity of Maryland, Baltimore · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We have developed a protocol regarding the genomic characterization of the MICA gene by next generation sequencing (NGS). The amplicon includes the full length of the gene and is about 13 kb. A total of 156 samples were included in the study. Ninety-seven of these samples were previously characterized at MICA by legacy methods (Sanger or sequence specific oligonucleotide) and were used to evaluate the accuracy, precision, specificity, and sensitivity of the assay. An additional 59 DNA samples of unknown ethnicity volunteers from the United States were only genotyped by NGS. Samples were chosen to contain a diverse set of alleles. Our NGS approach included a first round of sequencing on the Illumina MiSeq platform and a second round of sequencing on the MinION platform by Oxford Nanopore Technology (ONT), on selected samples for the purpose of either characterizing new alleles or setting phase among multiple polymorphisms to resolve ambiguities or generate complete sequence for alleles that were only partially reported in the IMGT/HLA database. Complete consensus sequences were generated for every allele sequenced with ONT, extending from the 5' untranslated region (UTR) to the 3' UTR of the MICA gene. Thirty-two MICA sequences were submitted to the IMGT/HLA database including either new alleles or filling up the gaps (exonic, intronic and/or UTRs) of already reported alleles. Some of the challenges associated with the characterization of these samples are discussed.

Indexed as

GenomicsHigh-Throughput Nucleotide SequencingAllelesGenotypeHumansSequence Analysis, DNAgenotypingIlluminaMICANGSOxford Nanopore

Identifiers

PMID32681760
PMCPMC7589345
OpenAlexW3042595250

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.