Evidence map›Paper›PMID 33193662›Full record

ArticleFrontiers in genetics2020

Whole-Exome Sequencing of Discordant Monozygotic Twin Families for Identification of Candidate Genes for Microtia-Atresia.

Xinmiao Fan, Lu Ping, Hao Sun, Yushan Chen, Pu Wang, Tao Liu, Rui Jiang, Xuegong Zhang, Xiaowei Chen

Abstract read
In one paragraph

Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Functional and Genetic Analyses Unveil the Implication ofJournal of developmental biology · 2026
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  5. International journal of molecular sciences · 2024
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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.

Xinmiao FanDepartment of Otolaryngology, Peking Union Medical College Hospital, Beijing, China.
Lu PingChinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Hao SunBioinformatics Division, BNRIST and MOE Key Laboratory of Bioinformatics, Department of Automation, Tsinghua University, Beijing, China.
Yushan ChenDepartment of Otolaryngology, The Ohio State University, Columbus, OH, United States.
Pu WangDepartment of Otolaryngology Head and Neck Surgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Tao LiuAnnoroad Gene Technology (Beijing) Co., Ltd, Beijing, China.
Rui JiangBioinformatics Division, BNRIST and MOE Key Laboratory of Bioinformatics, Department of Automation, Tsinghua University, Beijing, China.
Xuegong ZhangBioinformatics Division, BNRIST and MOE Key Laboratory of Bioinformatics, Department of Automation, Tsinghua University, Beijing, China.
Xiaowei ChenDepartment of Otolaryngology, Peking Union Medical College Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveWe used data from twins and their families to probe the genetic factors contributing to microtia-atresia, in particular, early post-twinning variations that potentially account for the discordant phenotypes of monozygotic twin pairs.

methodsSix families of monozygotic twins discordant for congenital microtia-atresia were recruited for study. The six patients shared a consistent clinical phenotype of unilateral microtia-atresia. Whole-exome sequencing (WES) was performed for all six twin pairs and their parents. Family segregation and multiple bioinformatics methods were applied to identify suspicious mutations in all families. Recurring mutations commonly detected in at least two families were highlighted. All variants were validated via Sanger sequencing. Gene Ontology (GO) analysis was performed to identify candidate gene sets and related pathways. Copy number variation (CNV), linkage analysis, association analysis and machine learning methods were additionally applied to isolate candidate mutations, and comparative genomics and structural modeling tools used to evaluate their potential roles in onset of microtia-atresia.

resultsOur analyses revealed 61 genes with suspected mutations associated with microtia-atresia. Five (

conclusionBased on comprehensive genetic and bioinformatic analyses of WES data from six families of discordant monozygotic twins with microtia-atresia, we identified multiple candidate genes that may function in post-twinning onset of the disease. The collective findings provide novel insights into the pathogenesis of congenital microtia-atresia.

Indexed as

bioinformatics analysisgenesmicrotia-atresiamonozygotic discordant twinswhole-exome sequencing

Identifiers

PMID33193662
PMCPMC7642525

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