Evidence map›Paper›PMID 28938720›Full record

ArticleGigaScience2017

Deep whole-genome sequencing of 90 Han Chinese genomes.

Tianming Lan, Haoxiang Lin, Wenjuan Zhu, Tellier Christian Asker Melchior Laurent, Mengcheng Yang, Xin Liu, Jun Wang, Jian Wang, Huanming Yang, Xun Xu and 1 more

Erratum issuedAbstract read
In one paragraph

Article in GigaScience, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
–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

26 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  12. Population-scale genotyping of structural variation in the era of long-read sequencing.Computational and structural biotechnology journal · 2022
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Tianming LanBGI-Shenzhen, Build 11, Beishan Industrial Zone, Yantian District, Shenzhen, 518083, China.
Haoxiang LinBGI Genomics, BGI-Shenzhen, Building NO. 7, BGI Park, No. 21 Hongan 3rd Street, Yantian District, Shenzhen, 518083, China.
Wenjuan ZhuBGI Genomics, BGI-Shenzhen, Building NO. 7, BGI Park, No. 21 Hongan 3rd Street, Yantian District, Shenzhen, 518083, China.
Tellier Christian Asker Melchior LaurentBGI-Shenzhen, Build 11, Beishan Industrial Zone, Yantian District, Shenzhen, 518083, China.
Mengcheng YangBGI-Shenzhen, Build 11, Beishan Industrial Zone, Yantian District, Shenzhen, 518083, China.
Xin LiuBGI-Shenzhen, Build 11, Beishan Industrial Zone, Yantian District, Shenzhen, 518083, China.
Jun WangBGI-Shenzhen, Build 11, Beishan Industrial Zone, Yantian District, Shenzhen, 518083, China.
Jian WangBGI-Shenzhen, Build 11, Beishan Industrial Zone, Yantian District, Shenzhen, 518083, China.
Huanming YangBGI-Shenzhen, Build 11, Beishan Industrial Zone, Yantian District, Shenzhen, 518083, China.
Xun XuBGI-Shenzhen, Build 11, Beishan Industrial Zone, Yantian District, Shenzhen, 518083, China.
Xiaosen GuoBGI-Shenzhen, Build 11, Beishan Industrial Zone, Yantian District, Shenzhen, 518083, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Next-generation sequencing provides a high-resolution insight into human genetic information. However, the focus of previous studies has primarily been on low-coverage data due to the high cost of sequencing. Although the 1000 Genomes Project and the Haplotype Reference Consortium have both provided powerful reference panels for imputation, low-frequency and novel variants remain difficult to discover and call with accuracy on the basis of low-coverage data. Deep sequencing provides an optimal solution for the problem of these low-frequency and novel variants. Although whole-exome sequencing is also a viable choice for exome regions, it cannot account for noncoding regions, sometimes resulting in the absence of important, causal variants. For Han Chinese populations, the majority of variants have been discovered based upon low-coverage data from the 1000 Genomes Project. However, high-coverage, whole-genome sequencing data are limited for any population, and a large amount of low-frequency, population-specific variants remain uncharacterized. We have performed whole-genome sequencing at a high depth (∼×80) of 90 unrelated individuals of Chinese ancestry, collected from the 1000 Genomes Project samples, including 45 Northern Han Chinese and 45 Southern Han Chinese samples. Eighty-three of these 90 have been sequenced by the 1000 Genomes Project. We have identified 12 568 804 single nucleotide polymorphisms, 2 074 210 short InDels, and 26 142 structural variations from these 90 samples. Compared to the Han Chinese data from the 1000 Genomes Project, we have found 7 000 629 novel variants with low frequency (defined as minor allele frequency < 5%), including 5 813 503 single nucleotide polymorphisms, 1 169 199 InDels, and 17 927 structural variants. Using deep sequencing data, we have built a greatly expanded spectrum of genetic variation for the Han Chinese genome. Compared to the 1000 Genomes Project, these Han Chinese deep sequencing data enhance the characterization of a large number of low-frequency, novel variants. This will be a valuable resource for promoting Chinese genetics research and medical development. Additionally, it will provide a valuable supplement to the 1000 Genomes Project, as well as to other human genome projects.

Indexed as

Genome, HumanAsian PeopleGene FrequencyHigh-Throughput Nucleotide SequencingHumansINDEL MutationPolymorphism, Single NucleotideWhole Genome Sequencingde novo assemblygenetic variationsHan Chinese genomeshigh-coverage whole-genome sequencing

Identifiers

PMID28938720
PMCPMC5603764

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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.