Evidence map›Paper›PMID 38972030›Full record

ArticleMolecular genetics and genomics : MGG2024

Unveiling novel genetic variants in 370 challenging medically relevant genes using the long read sequencing data of 41 samples from 19 global populations.

Yanfeng Ji, Junfan Zhao, Jiao Gong, Fritz J Sedlazeck, Shaohua Fan

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Molecular genetics and genomics : MGG, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Review
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.

Yanfeng JiState Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, School of Life Science, Fudan University, Shanghai, 200438, China.
Junfan ZhaoState Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, School of Life Science, Fudan University, Shanghai, 200438, China.
Jiao GongState Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, School of Life Science, Fudan University, Shanghai, 200438, China.
Fritz J SedlazeckHuman Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA. Fritz.Sedlazeck@bcm.edu.
Shaohua FanState Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, School of Life Science, Fudan University, Shanghai, 200438, China. shaohua_fan@fudan.edu.cn.ORCID http://orcid.org/0000-0003-0610-9106

Funding

Genomic Architecture of Common Disease in Diverse Populations: WGS of Ongoing Hemorrhagic Stroke Study SupplementUM1HG008898 · NHGRI · BAYLOR COLLEGE OF MEDICINE · PI GIBBS, RICHARD A · 2016 to 2020
$77.0M
Frequency of variants of unknown significance by ancestry groups in the All of Us Research Program cohortU01HG011758 · NHGRI · BAYLOR COLLEGE OF MEDICINE · PI RICHARD A GIBBS, JAMES R. LUPSKI · 2021 to 2026
$13.8M
Ministry of Science and Technology of the People's Republic of China 2020YFE0201600Ministry of Science and Technology of the People's Republic of China 2021YFC2500202National Institute of Health 1U01HG011758-01National Institute of Health UM1HG008898National Natural Science Foundation of China 31970563National Natural Science Foundation of China 32370686NHGRI NIH HHS U01 HG011758NHGRI NIH HHS UM1 HG008898
6 · The paper itself

Abstract

backgroundA large number of challenging medically relevant genes (CMRGs) are situated in complex or highly repetitive regions of the human genome, hindering comprehensive characterization of genetic variants using next-generation sequencing technologies. In this study, we employed long-read sequencing technology, extensively utilized in studying complex genomic regions, to characterize genetic alterations, including short variants (single nucleotide variants and short insertions and deletions) and copy number variations, in 370 CMRGs across 41 individuals from 19 global populations.

resultsOur analysis revealed high levels of genetic variants in CMRGs, with 68.73% exhibiting copy number variations and 65.20% containing short variants that may disrupt protein function across individuals. Such variants can influence pharmacogenomics, genetic disease susceptibility, and other clinical outcomes. We observed significant differences in CMRG variation across populations, with individuals of African ancestry harboring the highest number of copy number variants and short variants compared to samples from other continents. Notably, 15.79% to 33.96% of short variants were exclusively detectable through long-read sequencing. While the T2T-CHM13 reference genome significantly improved the assembly of CMRG regions, thereby facilitating variant detection in these regions, some regions still lacked resolution.

conclusionOur results provide an important reference for future clinical and pharmacogenetic studies, highlighting the need for a comprehensive representation of global genetic diversity in the reference genome and improved variant calling techniques to fully resolve medically relevant genes.

Indexed as

DNA Copy Number VariationsGenome, HumanHigh-Throughput Nucleotide SequencingGenetic Predisposition to DiseaseGenetics, PopulationGenetic VariationHumansINDEL MutationPolymorphism, Single NucleotideChallenging medically relevant genesCopy number variationGenome sequencingLong read sequencingShort insertion and deletionSingle nucleotide polymorphism

Identifiers

PMID38972030
PMCPMC11955097

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