Researchers released the human genome structural variation database and computational analysis platform

The team of Xu Shuhua, professor of the School of Life Sciences/Institute of Human Phenomics, Fudan University, Zhang Guoqing, researcher of the Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, and Fan Shaohua, researcher of the School of Life Sciences, Fudan University, collaborated to develop the human genome structural variation database PGG.
SV.

The team of Xu Shuhua, professor of the School of Life Sciences/Institute of Human Phenomics, Fudan University, Zhang Guoqing, researcher of the Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, and Fan Shaohua, researcher of the School of Life Sciences, Fudan University, collaborated to develop the human genome structural variation database PGG.
SV ( _istranslated="1"> 。 The research results are titled PGG.
SV: a whole-genome-sequencing-based structural variant resource and data analysis platform, published in Nucleic Acids Research
。 By collecting whole genome sequencing data of the global population, the database focuses on the mining and integration of genomic structural variation data, providing a comprehensive platform
for data acquisition, information query and online analysis for the study of human genome structural variation.

Genomic structural variants (SVs) mainly include DNA deletions, insertions, fragment duplications and other variant types
of large fragments on the genome.
Studies have shown that SV is associated with a variety of complex genetic diseases such as cancer, autism, and neurodevelopmental disorders, and has received continuous attention
in the fields of medicine and genetics in recent years.
With the advancement and popularization of genome sequencing technology, a large number of structural variants have been continuously discovered and studied, and some structural variants with strong pathogenicity have gradually been verified
.
This study aims to construct a representative and diverse dataset of genomic structural variation in healthy populations, on the one hand, to provide reliable control samples for the study of structural variation in patients with genetic diseases, and on the other hand, to annotate and predict the function of mutation will effectively narrow the screening scope of pathogenic mutations, and provide effective guidance and assistance
for research in related fields.

Due to the significant differences and diversity of structural variants in different regions and ethnic groups, and the existing databases and public datasets each adopt different analysis processes, there is a lack of structural variation resources and analysis platforms representative of population samples and next-generation sequencing data, especially the coverage of East Asian population samples
.
The scientific research team integrated large-scale sequencing data, including 6,048 whole genome sequencing data from 177 representative regions and ethnic groups around the world, especially for the in-depth analysis of China's rich ethnic diversity characteristics, covering 50 ethnic minorities
in China for the first time.
As of publication, the database contains a total of 584,277 structural variants, which will continue to be added
in the future.
In addition, PGG.
SV includes the third-generation long-reads sequencing data for the first time, which has greater advantages in the detection of structural variations, especially in the detection and determination of inserted sequences, and the effect is significantly better than second-generation sequencing technology
.
Previous databases of large-scale structural variants were built
on next-generation sequencing or gene chip data.
The research team generated and collected 1,030 third-generation sequencing genomes, and for the first time used the combination of third-generation sequencing and second-generation sequencing to construct a structural variation database, which greatly improved the quantity and quality
of structural variation detection results.

In terms of database function, PGG.
SV provides concise and friendly query functions, providing accurate display of the genomic location of different population structural variants and statistical information
such as frequency differences between various ethnic groups around the world.
Taking advantage of the previous accumulation of the research group, PGG.
SV linked with the PGG.
SNV and other databases previously developed by Xu Shuhua's team, and combined the detailed results of single nucleotide variation (SNV) with structural variation with the help of linkage imbalance and genomic spatial location information to enhance the analysis function
of data diversity 。 In addition, PGG.
SV provides rich clinical effect analysis and predictive analysis capabilities, providing predictive and enrichment analysis of potential phenotypes, functions and retrieval of relevant structural variants by specific diseases and phenotypes based on genes and regulatory elements associated with structural variants, so that users with clinical research needs can use
.

In addition, PGG.
SV supports rich online analysis and visualization capabilities
.
The research team provides comparisons and annotations of user-submitted structural variation results so that users can understand the differences between their target sample and the control sample provided by the database; Provides structural variation visualization capabilities that enable retrieval of user-submitted DNA sequences on the human genome, display genomic locations of relevant variants, and fine-grained visualization
of changes in the spatial structure of variations.

PGG.
SV provides high-quality population genomic structural variation data resources, greatly improves the detection and display of human genome structural variation information based on next-generation sequencing data, especially for the first time, it comprehensively covers the structural variation diversity of East Asian populations and Chinese populations, and provides annotations
of related genes and potential clinical effects.
In addition, the platform provides multiple online analysis capabilities, including case-control studies, as well as visualization tools
for structural variation in the human genome.