Oxford Nanopore Technology (ONT) third-generation sequencing (TGS) is a versatile genetic diagnostic platform. However, it is nonetheless challenging to prepare long-template libraries for long-read TGS, particularly the ONT method for analysis of hemoglobinopathy variants involving complex structures and occurring in GC-rich and/or homologous regions. A multiplex long PCR was designed to prepare library templates, including the whole-gene amplicons for HBA2/1, HBG2/1, HBD, and HBB, as well as the allelic amplicons for targeted deletions and special structural variations. Library construction was performed using long-PCR products, and sequencing was conducted on an Oxford Nanopore MinION instrument. Genotypes were identified based on integrative genomics viewer (IGV) plots. This novel long-read TGS method distinguished all single nucleotide variants and structural variants within HBA2/1, HBG2/1, HBD, and HBB based on the whole-gene sequence reads. Targeted deletions and special structural variations were also identified according to the specific allelic reads. The result of 158 α-/β-thalassemia samples showed 100% concordance with previously known genotypes. This ONT TGS method is high-throughput, which can be used for molecular screening and genetic diagnosis of hemoglobinopathies. The strategy of multiplex long PCR is an efficient strategy for library preparation, providing a practical reference for TGS assay development.

The importance of structural variants (SVs) for human phenotypes and diseases is now recognized. Although a variety of SV detection platforms and strategies that vary in sensitivity and specificity have been developed, few benchmarking procedures are available to confidently assess their performances in biological and clinical research. To facilitate the validation and application of these SV detection approaches, we established an Asian reference material by characterizing the genome of an Epstein-Barr virus (EBV)-immortalized B lymphocyte line along with identified benchmark regions and high-confidence SV calls. We established a high-confidence SV callset with 8938 SVs by integrating four alignment-based SV callers, including 109× Pacific Biosciences (PacBio) continuous long reads (CLRs), 22× PacBio circular consensus sequencing (CCS) reads, 104× Oxford Nanopore Technologies (ONT) long reads, and 114× Bionano optical mapping platform, and one de novo assembly-based SV caller using CCS reads. A total of 544 randomly selected SVs were validated by PCR amplification and Sanger sequencing, demonstrating the robustness of our SV calls. Combining trio-binning-based haplotype assemblies, we established an SV benchmark for identifying false negatives and false positives by constructing the continuous high-confidence regions (CHCRs), which covered 1.46 gigabase pairs (Gb) and 6882 SVs supported by at least one diploid haplotype assembly. Establishing high-confidence SV calls for a benchmark sample that has been characterized by multiple technologies provides a valuable resource for investigating SVs in human biology, disease, and clinical research.

Background: Tumor mutational burden (TMB) is a promising biomarker for stratifying patient subpopulation who would benefit from immune checkpoint blockade (ICB) therapies. Although great efforts have been made for standardizing TMB measurement, mutation calling and TMB quantification can be challenging in samples with low tumor content including liquid biopsies. The effect of varying tumor content on TMB estimation by different assay methods has never been systematically investigated.Method: We established a series of reference standard DNA samples derived from 11 pairs of tumor–normal matched human cell lines across different cancer types. Each tumor cell line was mixed with its matched normal at 0% (control), 1%, 2%, 5%, and 10% mass‐to‐mass ratio to mimic the clinical samples with low tumor content. TMB of these reference standards was evaluated by both ∼1000× whole‐exome sequencing (wesTMB) and targeted panel sequencing (psTMB) at four different vendors. Both regression and classification analyses of TMB were performed for theoretical investigation and clinical practice purposes.Results: Linear regression model was established that demonstrated in silico psTMB determined by regions of interest (ROI) as a great representative of wesTMB based on TCGA dataset. It was also true in our reference standard samples as the predicted psTMB interval based on the observed wesTMB captured the intended 90% of the in silico psTMB values. Although ∼1000× deep WES was applied, reference standard samples with less than 5% of tumor proportions are below the assay limit of detection (LoD) of wesTMB quantification. However, predicted wesTMB based on observed psTMB accurately classify (>0.97 AUC) for TMB high and low patient stratification even in samples with 2% of tumor content, which is more clinically relevant, as TMB determination should be a qualitative assay for TMB high and low patient classification. One targeted panel sequencing vendor using an optimized blood psTMB pipeline can further classify TMB status accurately (>0.82 AUC) in samples with only 1% of tumor content.Conclusions: We developed a linear model to establish the quantitative correlation between wesTMB and psTMB. A set of DNA reference standards was produced in aid to standardize TMB measurements in samples with low tumor content across different targeted sequencing panels. This study is a significant contribution aiming to harmonize TMB estimation and extend its future application in clinical samples with low tumor content including liquid biopsy.

Homologous recombination deficiency (HRD) has emerged as a critical prognostic and predictive biomarker in oncology. However, current testing methods, especially those reliant on targeted panels, are plagued by inconsistent results from the same samples. This highlights the urgent need for standardized benchmarks to evaluate HRD assay performance. In phases IIa and IIb of the Chinese HRD Harmonization Project, we developed ten pairs of well-characterized DNA reference materials derived from lung, breast, and melanoma cancer cell lines and their matched normal cell lines, keeping each paired with seven cancer-to-normal mass ratios. Reference datasets for allele-specific copy number variations (ASCNVs) and HRD scores were established and validated using three sequencing methods and nine analytical pipelines. The genomic instability scores (GISs) of the reference materials ranged from 11 to 96, enabling validation across various thresholds. The ASCNV reference datasets covered a genomic span of 2340 to 2749 Mb, equivalent to 81.2% to 95.4% of the autosomes in the 37d5 reference genome. These benchmarks were subsequently utilized to assess the accuracy and reproducibility of four HRD panel assays, revealing significant variability in both ASCNV detection and HRD scores. The concordance between panel-detected GISs and reference GISs ranged from 0.81 to 0.94, with only two assays exhibiting high overall agreement with Myriad MyChoice CDx for HRD classification. This study also identified specific challenges in ASCNV detection in HRD-related regions and the profound impact of high ploidy on consistency. The established HRD reference materials and datasets provide a robust toolkit for objective evaluation of HRD testing.

Objectives: Nanopore sequencing shows advantages in detecting single nucleotide variations (SNVs), deletions, and complex structural variants as a single test in thalassemia. However, the performance evaluation or verification of this method remains unestablished, which is essential before clinical utility and panel registration. Here, we developed a classification method for thalassemia mutations, enabling automated interpretation, visual representation, and identification of diverse mutation types.Methods: We used a total of 36 samples, comprising 32 reference materials and four clinical samples to assess the performance of nanopore sequencing in identifying variants in terms of concordance, precision, and the lower limits of detection.Results: Our analysis successfully identified 19 SNVs, six deletions, and two triplications using nanopore sequencing across all samples. Notably, these variants showed complete concordance of 100% with the genotypes of the reference materials and known results. The precision of nanopore sequencing for detecting thalassemia variants was consistently high, with neither false positive nor false negative observed. Furthermore, the lower limits of detection achieved in our study were 3 ng/μL.Conclusions: Overall, our study proved that the reference materials can be used to evaluate the performance of nanopore sequencing in identifying thalassemia mutations, and it is necessary to incorporate triplications when utilizing reference materials for performance evaluation of long‐read sequencing. The consistent and robust performance of nanopore sequencing in this study demonstrates its potential as a reliable method for comprehensive variant detection in thalassemia and other genetic diseases diagnosis.