iGeneTech Bioscience Co., Ltd.
EN

SARS-CoV-2 Panel

Get Quote
Overview
Performance
Cases
Ordering Info
Resources
Articles

Overview

iGeneTech Bioscience offers 2 full length SARS-CoV-2 genome capture solutions for COVID-19 surveillance and research by using hybridization capture and multiplex amplicon technologies.

SARS-CoV-2-Panel

Product Specification

Panel Number

T1302XV1(Hybridization Capture) A186XV6/V7 (Multiplex Amplicon)"

Technical Platform
T1302XV1: TargetSeq® Hybridization Capture Sequencing A186XV6/V7: MultipSeq® Multiplex Amplicon Sequencing
Coverage Size
T1302XV1:510.1 Mb A186XV6/V7:29.8 kb
Reference Database
NCBI/Taxonomy
Reference Genome
10,000 full-length sequences of SARS-CoV-2 genome
Coverage
SARS-CoV-2 genome full length
Storage

T1302XV1: -20℃±5℃  A186XV6/V7:-20℃±5℃

Sequence Platform
T1302XV1:Illumina / MGI A186XV6:Illumina A186XV7:MGI
Recommend Sequencing Read Length
PE150
Recommend Sequencing Data Size and Depth
T1302XV1:2 Gb A186XV6/V7:0.2 Gb


Advantages

  • 99.9% coverage of SARS-CoV-2 genome for a comprehensive understanding of the virus.

  • It is suitable for a wide range of samples, such as nasopharyngeal swabs, deep sputum, alveolar lavage fluid, lung tissue biopsy specimens, etc.

  • High sensitivity MultipSeq® multiplex amplicon technology allows detection limits as low as 50 copies.

  • Updating panel according to the latest database for known and novel strains.



Learn More About SARS-CoV-2 Panel

Performance

Excellent Performance for TargetSeq® Option

With the proven TargetSeq One® workflow, test results showed high coverage and uniformity for TargetSeq® option.

excellent-performance-for-targetseq-option.png

High Sensitivity for MultipSeq® Option

Test results of MultipSeq® multiplex amplicon option with COVID-19 full length standard sample (Gene-Well, cat.TEST09) showed extremely high detection sensitivity.

SampleInput (Copies)Raw Data (Mb)Data Efficiency (%)Mapping Rate (%)Capture Rate (%)1X Coverage Rate (%)Average Sequencing Depth100X Coverage Rate (%)20%X Coverage Rate (%)
Sample52200077.8895.4996.941001002461.2899.2393.31
Sample62200169.3595.5495.531001005325.7699.2196.66
Sample7220160.675.4666.181001003471.3799.3596.68
Sample822212.2646.4322.31001001521.0798.2179.77
Sample92218.7637.418.6610098.99606.2892.5980.63


Cases

Molecular Cell
Molecular Cell

Analysis of the genome of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) from clinical samples is critical to understanding virus transmission and evolution and vaccine development. Existing RNA sequencing methods are technically and time-demanding for users and are not applicable to time-sensitive clinical samples, and not optimized for the high performance of the viral genome. In this study, full-length capture of coronavirus was performed after library construction of clinical samples by capture technology, and a complete high-depth, high-coverage SARS-CoV-2 genome with high yield and stability was successfully obtained. By reducing the hands-on time from sample to viral enrichment sequencing library, this rapid, versatile, and clinically friendly method will facilitate molecular epidemiological studies during current and future outbreaks.

Nature Communications
Nature Communications

The spread of SARS-CoV-2 in Beijing by May 2020 was caused by domestic and global transmission of imported cases. The study reported genomic surveillance data from 102 imported cases, which indicated that all cases in Beijing could be broadly classified into three categories: Wuhan exposure, local transmission, and overseas importation. The study classified all sequenced genomes into seven clusters based on representative high-frequency single nucleotide polymorphisms (SNPs). Genomic comparisons showed that the input group had higher genomic diversity than the Wuhan-exposed and locally transmitted groups, suggesting continued genomic evolution during global transmission. The input group had region-specific SNPs, whereas single nucleotide variants within the host showed a random character with no significant differences between groups. The epidemiological data suggest that case detection in a mandatory quarantine entry situation may be an effective method to prevent the recurrence of outbreaks triggered by imported cases. Notably, the study also identified a novel set of insertions/deletions (InDel). The data from this study suggest that the SARS-CoV-2 genome may have high mutation tolerance.

Ordering Info

SARS-CoV-2 Panel
Product NamePanel NumberSetCat. No
TargetSeq® SARS-Cov-2 Panel

T1302XV1

16 rxn

PH2001721

96 rxn

PH2001722

MultipSeq® SARS-CoV-2 Research Assay (for Illumina)A186XV616 rxnM62111
96 rxnM62112
960 rxnM62113
MultipSeq® SARS-CoV-2 Research Assay (for MGI DI)A186XV716 rxnM62121
96 rxnM62122
960 rxnM62123


Resources

Demo DataSet
  • TargetSeq® SARS-CoV-2 Panel (T1302XV1) demo data
    TargetSeq® SARS-CoV-2 Panel (T1302XV1) demo data
  • MultipSeq® SARS-CoV-2 Research Assay (for MGI DI, A186XV7) demo data
    MultipSeq® SARS-CoV-2 Research Assay (for MGI DI, A186XV7) demo data
  • MultipSeq® SARS-CoV-2 Research Assay (for Illumina, A186XV6) demo data
    MultipSeq® SARS-CoV-2 Research Assay (for Illumina, A186XV6) demo data
bed File
  • TargetSeq® SARS-CoV-2 Panel (T1302XV1) bed file
    TargetSeq® SARS-CoV-2 Panel (T1302XV1) bed file
  • MultipSeq® SARS-CoV-2 Research Assay (for MGI DI, A186XV7) bed file
    MultipSeq® SARS-CoV-2 Research Assay (for MGI DI, A186XV7) bed file
  • MultipSeq® SARS-CoV-2 Research Assay (for Illumina, A186XV6) bed file
    MultipSeq® SARS-CoV-2 Research Assay (for Illumina, A186XV6) bed file

Articles

Chen Chen; Jizhou Li; Lin Di; Qiuyu Jing; Pengcheng Du; Chuan Song; Jiarui Li; Qiong Li; Yunlong Cao; X. Sunney Xie; Angela R. Wu; Hui Zeng; Yanyi Huang; Jianbin Wang
Molecular Cell 2020;80(6):1123-1134.e4 DOI:10.1016/j.molcel.2020.11.030
Pengcheng Du; Nan Ding; Jiarui Li; Fujie Zhang; Qi Wang; Zhihai Chen; Chuan Song; Kai Han; Wen Xie; Jingyuan Liu; Linghang Wang; Lirong Wei; Shanfang Ma; Mingxi Hua; Fengting Yu; Lin Wang; Wei Wang; Kang An; Jianjun Chen; Haizhou Liu; Guiju Gao; Sa Wang; Yanyi Huang; Angela R. Wu; Jianbin Wang; Di Liu; Hui Zeng; Chen Chen
Nature Communications 2020;11(1):5503 DOI:10.1038/s41467-020-19345-0
Jiarui Li; Pengcheng Du; Lijiang Yang; Ju Zhang; Chuan Song; Danying Chen; Yangzi Song; Nan Ding; Mingxi Hua; Kai Han; Rui Song; Wen Xie; Zhihai Chen; Xianbo Wang; Jingyuan Liu; Yanli Xu; Guiju Gao; Qi Wang; Lin Pu; Lin Di; Jie Li; Jinglin Yue; Junyan Han; Xuesen Zhao; Yonghong Yan; Fengting Yu; Angela R. Wu; Fujie Zhang; Yi Qin Gao; Yanyi Huang; Jianbin Wang; Hui Zeng; Chen Chen
Cell Reports 2021;38(2):110205 DOI:10.1016/j.celrep.2021.110205
Xinghuo Pang; Lili Ren; Shuangsheng Wu; Wentai Ma; Jian Yang; Lin Di; Jie Li; Yan Xiao; Lu Kang; Shichang Du; Jing Du; Jing Wang; Gang Li; Shuguang Zhai; Lijuan Chen; Wenxiong Zhou; Shengjie Lai; Lei Gao; Yang Pan; Quanyi Wang; Mingkun Li; Jianbin Wang; Yanyi Huang; Jianwei Wang
National Science Review 2020;7(12):1861-1864 DOI:10.1093/nsr/nwaa264
Yi Xu; Lu Kang; Zijie Shen; Xufang Li; Weili Wu; Wentai Ma; Chunxiao Fang; Fengxia Yang; Xuan Jiang; Sitang Gong; Li Zhang; Mingkun Li
Journal of Genetics and Genomics 2020;47(10):610-617 DOI:10.1016/j.jgg.2020.10.002
Ju Zhang; Nan Ding; Yangzi Song; Rui Song; Yang Pan; Linghang Wang; Shuo Yan; Qi Wang; Shanfang Ma; Lirong Wei; Fengting Yu; Lianhe Lu; Fujie Zhang; Chen Chen; Hui Zeng
The Innovation 2021;2(2):100099 DOI:10.1016/j.xinn.2021.100099