Structural variants in the Chinese population and their impact on phenotypes, diseases and population adaptation

AbstractA complete characterization of genetic variation is a fundamental goal of human genome research. Long-read sequencing has improved the sensitivity of structural variant discovery. Here, we conduct the long-read sequencing-based structural variant analysis for 405 unrelated Chinese individuals, with 68 phenotypic and clinical measurements. We discover a landscape of 132,312 nonredundant structural variants, of which 45.2% are novel. The identified structural variants are of high-quality, with an estimated false discovery rate of 3.2%. The concatenated length of all the structural variants is approximately 13.2% of the human reference genome. We annotate 1,929 loss-of-function structural variants affecting the coding sequence of 1,681 genes. We discover rare deletions in HBA1/HBA2/HBB associated with anemia. Furthermore, we identify structural variants related to immunity which differentiate the northern and southern Chinese populations. Our study describes the landscape of structural variants in the Chinese population and their contribution to phenotypes and disease.

Download Full-text

Structural variants in Chinese population and their impact on phenotypes, diseases and population adaptation

10.1101/2021.02.09.430378 ◽

2021 ◽

Author(s):

Zhikun Wu ◽

Zehang Jiang ◽

Tong Li ◽

Chuanbo Xie ◽

Liansheng Zhao ◽

...

Keyword(s):

Chinese Population ◽

Body Height ◽

Complete Characterization ◽

Loss Of Function ◽

New Associations ◽

Human Genomes ◽

Fundamental Goal ◽

Long Read ◽

Complex Landscape ◽

Clinical Measurements

SummaryA complete characterization of genetic variation is a fundamental goal of human genome research. Long-read sequencing (LRS) improves the sensitivity for structural variant (SV) discovery and facilitates a better understanding of the SV spectrum in human genomes. Here, we conduct the first LRS-based SV analysis in Chinese population. We perform whole-genome LRS for 405 unrelated Chinese, with 68 phenotypic and clinical measurements. We discover a complex landscape of 132,312 non-redundant SVs, of which 53.3% are novel. The identified SVs are of high-quality validated by the PacBio high-fidelity sequencing and PCR experiments. The total length of SVs represents approximately 13.2% of the human reference genome. We annotate 1,929 loss-of-function SVs affecting the coding sequences of 1,681 genes. We discover new associations of SVs with phenotypes and diseases, such as rare deletions in HBA1/HBA2/HBB associated with anemia and common deletions in GHR associated with body height. Furthermore, we identify SV candidates related to human immunity that differentiate sub-populations of Chinese. Our study reveals the complex landscape of human SVs in unprecedented detail and provides new insights into their roles contributing to phenotypes, diseases and evolution. The genotypic and phenotypic resource is freely available to the scientific community.

Download Full-text

Critical length in long-read resequencing

NAR Genomics and Bioinformatics ◽

10.1093/nargab/lqz027 ◽

2020 ◽

Vol 2 (1) ◽

Cited By ~ 1

Author(s):

Wouter De Coster ◽

Mojca Strazisar ◽

Peter De Rijk

Keyword(s):

Best Practice ◽

Critical Length ◽

Read Length ◽

Structural Variants ◽

Short Read ◽

Structural Variant ◽

Variant Discovery ◽

Human Genomes ◽

Long Reads ◽

Long Read

Abstract Long-read sequencing has substantial advantages for structural variant discovery and phasing of variants compared to short-read technologies, but the required and optimal read length has not been assessed. In this work, we used long reads simulated from human genomes and evaluated structural variant discovery and variant phasing using current best practice bioinformatics methods. We determined that optimal discovery of structural variants from human genomes can be obtained with reads of minimally 20 kb. Haplotyping variants across genes only reaches its optimum from reads of 100 kb. These findings are important for the design of future long-read sequencing projects.

Download Full-text

Critical length in long read resequencing

10.1101/621862 ◽

2019 ◽

Author(s):

De Coster Wouter ◽

Strazisar Mojca ◽

De Rijk Peter

Keyword(s):

Best Practice ◽

Critical Length ◽

Read Length ◽

Structural Variants ◽

Short Read ◽

Structural Variant ◽

Variant Discovery ◽

Human Genomes ◽

Long Reads ◽

Long Read

AbstractLong read sequencing has a substantial advantage for structural variant discovery and phasing of variants compared to short-read technologies, but the required and optimal read length has not been assessed. In this work, we used simulated long reads and evaluated structural variant discovery and variant phasing using current best practice bioinformatics methods. We determined that optimal discovery of structural variants from human genomes can be obtained with reads of minimally 15 kbp. Haplotyping genes entirely only reaches its optimum from reads of 100 kbp. These findings are important for the design of future long read sequencing projects.

Download Full-text

NyuWa Genome Resource: Deep Whole Genome Sequencing Based Chinese Population Variation Profile and Reference Panel

10.1101/2020.11.10.376574 ◽

2020 ◽

Author(s):

Peng Zhang ◽

Huaxia Luo ◽

Yanyan Li ◽

You Wang ◽

Jiajia Wang ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Chinese Population ◽

Population Variation ◽

Reference Panel ◽

Specific Reference ◽

Whole Genome ◽

Loss Of Function ◽

Southern Chinese ◽

Novel Variants

AbstractThe lack of Chinese population specific haplotype reference panel and whole genome sequencing resources has greatly hindered the genetics studies in the world’s largest population. Here we presented the NyuWa genome resource of 71.1M SNPs and 8.2M indels based on deep (26.2X) sequencing of 2,999 Chinese individuals, and constructed NyuWa reference panel of 5,804 haplotypes and 19.3M variants, which is the first publicly available Chinese population specific reference panel with thousands of samples. There were 25.0M novel variants in NyuWa genome resource, and 3.2M specific variants in NyuWa reference panel. Compared with other panels, NyuWa reference panel reduces the Han Chinese imputation error rate by the range of 30% to 51%. Population structure and imputation simulation tests supported the applicability of one integrated reference panel for both northern and southern Chinese. In addition, a total of 22,504 loss-of-function variants in coding and noncoding genes were identified, including 11,493 novel variants. These results highlight the value of NyuWa genome resource to facilitate genetics research in Chinese and Asian populations.

Download Full-text

TSD: A computational tool to study the complex structural variants using PacBio targeted sequencing data

10.1101/474445 ◽

2018 ◽

Author(s):

Guofeng Meng ◽

Ying Tan ◽

Yue Fan ◽

Yan Wang ◽

Guang Yang ◽

...

Keyword(s):

Human Cell Line ◽

Targeted Sequencing ◽

Structural Variants ◽

Sequencing Data ◽

Rna Sequences ◽

Variant Discovery ◽

Powerful Approach ◽

Full Profile ◽

Long Read ◽

Complex Structural

ABSTRACTThe PacBio sequencing is a powerful approach to study the DNA or RNA sequences in a longer scope. It is especially useful in exploring the complex structural variants generated by random integration or multiple rearrangement of internal or external sequences. However, there is still no tool designed to uncover their structural organization in the host genome. Here, we present a tool, TSD, for complex structural variant discovery using PacBio targeted sequencing data. It allows researchers to identify and visualize the genomic structures of targeted sequences by unlimited splitting, alignment and assembly of long PacBio reads. Application to the sequencing data derived from an HBV integrated human cell line(PLC/PRF/5) indicated that TSD could recover the full profile of HBV integration events, especially for the regions with the complex human-HBV genome integrations and multiple HBV rearrangements. Compared to other long read analysis tools, TSD showed a better performance for detecting complex genomic structural variants. TSD is publicly available at: https://github.com/menggf/tsd

Download Full-text

SVIM: structural variant identification using mapped long reads

Bioinformatics ◽

10.1093/bioinformatics/btz041 ◽

2019 ◽

Vol 35 (17) ◽

pp. 2907-2915 ◽

Cited By ~ 32

Author(s):

David Heller ◽

Martin Vingron

Keyword(s):

Single Molecule ◽

Simulated Data ◽

Supplementary Information ◽

Nucleotide Polymorphisms ◽

Structural Variants ◽

Human Phenotype ◽

Structural Variant ◽

Pacific Biosciences ◽

Sequencing Technologies ◽

Long Read

Abstract Motivation Structural variants are defined as genomic variants larger than 50 bp. They have been shown to affect more bases in any given genome than single-nucleotide polymorphisms or small insertions and deletions. Additionally, they have great impact on human phenotype and diversity and have been linked to numerous diseases. Due to their size and association with repeats, they are difficult to detect by shotgun sequencing, especially when based on short reads. Long read, single-molecule sequencing technologies like those offered by Pacific Biosciences or Oxford Nanopore Technologies produce reads with a length of several thousand base pairs. Despite the higher error rate and sequencing cost, long-read sequencing offers many advantages for the detection of structural variants. Yet, available software tools still do not fully exploit the possibilities. Results We present SVIM, a tool for the sensitive detection and precise characterization of structural variants from long-read data. SVIM consists of three components for the collection, clustering and combination of structural variant signatures from read alignments. It discriminates five different variant classes including similar types, such as tandem and interspersed duplications and novel element insertions. SVIM is unique in its capability of extracting both the genomic origin and destination of duplications. It compares favorably with existing tools in evaluations on simulated data and real datasets from Pacific Biosciences and Nanopore sequencing machines. Availability and implementation The source code and executables of SVIM are available on Github: github.com/eldariont/svim. SVIM has been implemented in Python 3 and published on bioconda and the Python Package Index. Supplementary information Supplementary data are available at Bioinformatics online.

Download Full-text

SVCollector: Optimized sample selection for validating and long-read resequencing of structural variants

10.1101/342386 ◽

2018 ◽

Cited By ~ 3

Author(s):

Fritz J. Sedlazeck ◽

Zachary Lemmon ◽

Sebastian Soyk ◽

William J. Salerno ◽

Zachary Lippman ◽

...

Keyword(s):

Sample Selection ◽

Supplementary Information ◽

Structural Variants ◽

Structural Variations ◽

Short Read Sequencing ◽

Variant Discovery ◽

Large Numbers ◽

Long Read ◽

Supplementary Material ◽

Selection For

AbstractSummaryStructural Variations (SVs) are increasingly recognized for their importance in genomics. Short-read sequencing is the most widely-used approach for genotyping large numbers of samples for SVs but suffers from relatively poor accuracy. Here we present SVCollector, an open-source method that optimally selects samples to maximize variant discovery and validation using long read resequencing or PCR-based validation. SVCollector has two modes: selecting those samples that are individually the most diverse or those that collectively capture the largest number of variations.Availabilityhttps://github.com/fritzsedlazeck/[email protected] informationSupplementary data are available at Bioinformatics online.

Download Full-text

SVIM: Structural Variant Identification using Mapped Long Reads

10.1101/494096 ◽

2018 ◽

Cited By ~ 2

Author(s):

David Heller ◽

Martin Vingron

Keyword(s):

Single Molecule ◽

Simulated Data ◽

Structural Variants ◽

Human Phenotype ◽

Structural Variant ◽

Small Indels ◽

Sequencing Technologies ◽

Long Reads ◽

Oxford Nanopore ◽

Long Read

AbstractMotivationStructural variants are defined as genomic variants larger than 50bp. They have been shown to affect more bases in any given genome than SNPs or small indels. Additionally, they have great impact on human phenotype and diversity and have been linked to numerous diseases. Due to their size and association with repeats, they are difficult to detect by shotgun sequencing, especially when based on short reads. Long read, single molecule sequencing technologies like those offered by Pacific Biosciences or Oxford Nanopore Technologies produce reads with a length of several thousand base pairs. Despite the higher error rate and sequencing cost, long read sequencing offers many advantages for the detection of structural variants. Yet, available software tools still do not fully exploit the possibilities.ResultsWe present SVIM, a tool for the sensitive detection and precise characterization of structural variants from long read data. SVIM consists of three components for the collection, clustering and combination of structural variant signatures from read alignments. It discriminates five different variant classes including similar types, such as tandem and interspersed duplications and novel element insertions. SVIM is unique in its capability of extracting both the genomic origin and destination of duplications. It compares favorably with existing tools in evaluations on simulated data and real datasets from PacBio and Nanopore sequencing machines.Availability and implementationThe source code and executables of SVIM are available on Github: github.com/eldariont/svim. SVIM has been implemented in Python 3 and published on bioconda and the Python Package [email protected]

Download Full-text

Structural variants identified by Oxford Nanopore PromethION sequencing of the human genome

10.1101/434118 ◽

2018 ◽

Cited By ~ 9

Author(s):

De Coster Wouter ◽

De Roeck Arne ◽

De Pooter Tim ◽

D’Hert Svenn ◽

De Rijk Peter ◽

...

Keyword(s):

Variant Calling ◽

High Sensitivity ◽

Structural Variants ◽

Computationally Efficient ◽

Sequencing Platform ◽

Structural Variant ◽

Oxford Nanopore ◽

Sequencing Studies ◽

Long Read

AbstractWe sequenced the Yoruban NA19240 genome on the long read sequencing platform Oxford Nanopore PromethION for benchmarking and evaluation of recently published aligners and structural variant calling tools. In this work, we determined the precision and recall, present high confidence and high sensitivity call sets of variants and discuss optimal parameters. The aligner Minimap2 and structural variant caller Sniffles are both the most accurate and the most computationally efficient tools in our study. We describe our scalable workflow for identification, annotation, and characterization of tens of thousands of structural variants from long read genome sequencing of an individual or population. By discussing the results of this genome we provide an approximation of what can be expected in future long read sequencing studies aiming for structural variant identification.

Download Full-text

HKG: An open genetic variant database of 205 Hong Kong Cantonese exomes

10.1101/2021.06.15.448515 ◽

2021 ◽

Author(s):

Min Ou ◽

Henry Chi-Ming Leung ◽

Amy Wing-Sze Leung ◽

Ho-Ming Luk ◽

Bin Yan ◽

...

Keyword(s):

Hong Kong ◽

Population Characteristics ◽

Good Representation ◽

Loss Of Function ◽

Sequencing Data ◽

Effective Population ◽

Chinese Populations ◽

Southern Chinese ◽

Hong Kong Cantonese ◽

Variant Database

HKG is the first fully accessible variant database for Hong Kong Cantonese, constructed from 205 novel whole-exome sequencing data. There has long been a research gap in the understanding of the genetic architecture of southern Chinese subgroups, including Hong Kong Cantonese. HKG detected 196,325 high-quality variants with 5.93% being novel, and 25,472 variants were found to be unique in HKG compared to other Chinese populations (CHN). PCA illustrates the uniqueness of HKG in CHN, and IBD analysis revealed that it is related mostly to southern Chinese with a similar effective population size. An admixture study estimated the ancestral composition of HKG and CHN, with a gradient change from north to south, consistent with their geological distribution. ClinVar, CIViC and PharmGKB annotated 599 clinically significant variants and 360 putative loss-of-function variants, substantiating our understanding of population characteristics for future medical development. Among the novel variants, 96.57% were singleton and 6.85% were of high impact. With a good representation of Hong Kong Cantonese, we demonstrated better variant imputation using reference with the addition of HKG data, thus successfully filling the data gap in southern Chinese to facilitate the regional and global development of population genetics.

Download Full-text