Evidence map›Paper›PMID 32274588›Full record

ArticleMolecular genetics and genomics : MGG2020

De novo genome assembly of a Han Chinese male and genome-wide detection of structural variants using Oxford Nanopore sequencing.

Ruikun Cai, Yichao Dong, Mingxia Fang, Changlong Guo, Xu Ma

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Article in Molecular genetics and genomics : MGG, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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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.

Ruikun CaiNational Research Institute for Family Planning, Beijing, 100081, China.ORCID http://orcid.org/0000-0001-9810-7559
Yichao DongNational Research Institute for Family Planning, Beijing, 100081, China.
Mingxia FangNational Research Institute for Family Planning, Beijing, 100081, China.
Changlong GuoNational Research Institute for Family Planning, Beijing, 100081, China. guochanglong723@aliyun.com.
Xu MaNational Research Institute for Family Planning, Beijing, 100081, China. genetic88@126.com.

Funding

the National Key Research and Development Program 2016YFC1000300the National Key Research and Development Program 2016YFC1000307the National Key Research and Development Program 2016YFC1000803the National Key Research and Development Program 2017YFC1002000the Non-profit Central Research Institute Fund of National Research Institute For Family Planning 2019GJM04
6 · The paper itself

Abstract

Advances in third-generation sequencing technologies provide an opportunity to investigate the complex organizational structure of the genome and unravel the genetic mechanisms of disease and physiological traits. Here we report the sequencing and de novo assembly of a healthy male northern Han Chinese genome and detection of structural variants using only nanopore sequencing data. We performed de novo assembly after filtering the raw data. Then, we aligned the assembled contigs to the human reference genome, and visualized chromosomes plot, which illustrated the contiguity of the nanopore assembly. Additionally, genomic structural variants were detected using a structure variation detection tool with long-read sequencing data. Median coverage depth was 30-fold and the read N50 was 27,136 bp. 96.51% of reads had at least one alignment to the human reference genome. The final assembled genome was 2.85 GB in size, with an N50 contig size of 5.4 MB. We identified 20,085 structural variants. Third-generation sequencing technologies have many advantages in de novo whole-genome assembly and detection of structural variants. Our results provide reference data for disease research, and can be used as a novel population-specific dataset of structural variants to support the efficient development of personalized precision medicine.

Indexed as

Nanopore SequencingAsian PeopleChromosomesGenome, HumanGenomicsGenomic Structural VariationHigh-Throughput Nucleotide SequencingHumansMalePrecision MedicineDe novo assemblyGenomic structural variationNanopore sequencingPrecision medicineThird-generation sequencing technologies

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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.