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    Research Services

    Target Region Sequencing

    Overview

    Targeted Region Sequencing focuses on a subset of genes or specific regions of the genome, which are most likely to be involved in the phenotype under study. Targeted sequencing is a cost-effective method for investigating areas of interest, and can also deliver much higher coverage levels, allowing identification of rare variants. Novogenes’s human targeted region sequencing (hTRS) provides comprehensive services for your project with custom panel design based on regions or genes of your interest, capture of target regions, sequencing and bioinformatic analysis.

    Service Specifications

    Applications

  • Cancer research
  • Human population studies
  • Linkage analysis for inherited diseases
  • Discovery of biomarkers and therapeutic targets
  • Advantages

  • Unsurpassed data quality: We guarantee a Q30 score ≥80%, exceeding Illumina’s official guarantee of ≥75%. See our data example.
  • Accurate variant calling with longer read length up to 150 bp.
  • Extraordinary informatics expertise: Novogene uses its cutting-edge bioinformatics pipeline and internationally recognized best-in-class software to provide customers with publication-ready data.
  • Sample Requirements

    Sample Type
    Amount (Qubit®)
    Purity
    Genomic DNA
    ≥400 ng
    OD260/280=1.8-2.0;
    MDA product/Single Cell Amplified DNA
    ≥1 μg
    Genomic DNA from FFPE *
    ≥0.8 μg
    cfDNA / ctDNA
    ≥50 ng
    Fragments should be in multiples of 170bp, with no genomic contamination

    Sequencing Parameters And Analysis Contents

    Platform Type
    Illumina Novaseq 6000
    Read Length
    Paired-end 150 bp
    Recommended sequencing depth
    Above 200× (Average effective sequencing depth)
    Standard analysis
    Data quality control
    Alignment with reference genome, statistics of sequencing depth and coverage
    SNP and InDel calling, annotation and statistics
    Somatic SNP/InDel/CNV calling, annotation and statistics (paired tumor samples)

    注:詳細については、サービス仕様をご参照ください。カスタマイズされたリクエストについては、お問い合わせください

    Project Workflow

    Genomic sequencing identifies WNK2 as a driver in hepatocellular carcinoma and a risk factor for early recurrence (Zhou et al., 2019)

    Background:

    Hepatocellular carcinoma (HCC) is a relatively common type of cancer with rising incidence and mortality rates. Although advances in the treatment and management of patients with HCC have improved survival rates, HCC still has a high rate of early recurrence. This study aimed to systematically define genomic alterations in Chinese patients with HCC and to identify mutations associated with early tumor recurrence in those patients.

    Sampling:

    • 182 Chinese primary HCC samples

    Sequencing Strategy:

    • Human whole genome sequencing (49 cases), whole exome sequencing (18 cases), and targeted region sequencing (115 cases) on Illumina platforms (PE150)

    Results & Conclusion

    By using WGS, this study described the genomic landscape, including somatic SNVs/InDels, CNVs, and SVs, and identified five prominent mutational signatures in 49 Chinese patients with HCC (Figure 1). Through WGS, WES, and targeted sequencing of 182 primary HCC samples, the results suggest that WNK2, RUNX1T1, CTNNB1, TSC1, and TP53 may play roles in HCC invasion and metastasis, and that WNK2 had the most significant difference in mutation frequency (Figure 2). Biofunctional investigations revealed a tumor-suppressor role for WNK2; its inactivation led to ERK1/2 signaling activation in HCC cells, tumor-associated macrophage infiltration, and tumor growth and metastasis. This study describes the genomic events that characterize Chinese HCCs and identify WNK2 as a driver of HCC that was associated with early tumor recurrence after curative resection.

    Figure 1. Genomic alterations and mutational signatures in 49 Chinese primary HCCs that had tumor early recurrence.

    Figure 2. The mutational spectrum in HCCs with or without early recurrence.

    Sequencing error rate distribution


    Note: The x-axis represents position in reads, and the y-axis represents the average error rate of bases of all reads at a position.


    GC content distribution


    Note: The x-axis is position in reads, and the y-axis is percentage of each type of bases (A, T, G, C); different bases are distinguishable by different colors.


    Sequencing depth & coverage distribution


    Note: Average sequencing depth (bar plot) and coverage (dot-line plot) in each chromosome. The x-axis represents chromosome; the left y-axis is the average depth; the right y-axis is the coverage (proportion of covered bases).


    SNP detection

    Sample
    Sample_1
    Sample_2
    Sample_3
    Sample_4
    Sample_5
    CDS
    22948
    22726
    22681
    22679
    22496
    Synonymous SNP
    11491
    11441
    11416
    11408
    11532
    missense SNP
    10697
    10657
    10628
    10639
    10359
    stopgain
    91
    87
    87
    87
    79
    stoploss
    12
    12
    12
    13
    15
    unknown
    564
    535
    544
    536
    520
    itronic
    130230
    128685
    129046
    132820
    182248
    UTR3
    6431
    6217
    6301
    6413
    7612
    UTR5
    3177
    3150
    3163
    3234
    3730
    splicing
    81
    81
    81
    81
    76
    ncRNA exonic
    3328
    3289
    3312
    3343
    4037
    ncRNA intronic
    11066
    10967
    10946
    11426
    17658
    ncRNA splicing
    8
    10
    13
    13
    13
    upstream
    4488
    4204
    4270
    4458
    6344
    downstream
    2392
    2352
    2436
    2406
    3501
    intergenic
    66631
    64399
    64589
    68470
    137307
    Total
    250922
    246335
    247081
    255588
    385335

    Heatmap of significantly mutated genes