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A novel framework for human leukocyte antigen (HLA) genotyping using probe capture-based targeted next-generation sequencing and computational analysis.
Lai, Sheng-Kai; Luo, Allen Chilun; Chiu, I-Hsuan; Chuang, Hui-Wen; Chou, Ting-Hsuan; Hung, Tsung-Kai; Hsu, Jacob Shujui; Chen, Chien-Yu; Yang, Wei-Shiung; Yang, Ya-Chien; Chen, Pei-Lung.
Afiliação
  • Lai SK; Genome and Systems Biology Degree Program, Academia Sinica and National Taiwan University, Taipei, Taiwan.
  • Luo AC; Department of Medical Genetics, National Taiwan University Hospital, Taipei, Taiwan.
  • Chiu IH; Department of Medical Genetics, National Taiwan University Hospital, Taipei, Taiwan.
  • Chuang HW; Department of Medical Genetics, National Taiwan University Hospital, Taipei, Taiwan.
  • Chou TH; Graduate Institute of Medical Genomics and Proteomics, College of Medicine, National Taiwan University, Taipei, Taiwan.
  • Hung TK; Graduate Institute of Medical Genomics and Proteomics, College of Medicine, National Taiwan University, Taipei, Taiwan.
  • Hsu JS; Graduate Institute of Medical Genomics and Proteomics, College of Medicine, National Taiwan University, Taipei, Taiwan.
  • Chen CY; Graduate Institute of Medical Genomics and Proteomics, College of Medicine, National Taiwan University, Taipei, Taiwan.
  • Yang WS; Department of Biomechatronics Engineering, National Taiwan University, Taipei, Taiwan.
  • Yang YC; Graduate Institute of Medical Genomics and Proteomics, College of Medicine, National Taiwan University, Taipei, Taiwan.
  • Chen PL; Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan.
Comput Struct Biotechnol J ; 23: 1562-1571, 2024 Dec.
Article em En | MEDLINE | ID: mdl-38650588
ABSTRACT
Human leukocyte antigen (HLA) genes play pivotal roles in numerous immunological applications. Given the immense number of polymorphisms, achieving accurate high-throughput HLA typing remains challenging. This study aimed to harness the human pan-genome reference consortium (HPRC) resources as a potential benchmark for HLA reference materials. We meticulously annotated specific four field-resolution alleles for 11 HLA genes (HLA-A, -B, -C, -DPA1, -DPB1, -DQA1, -DQB1, -DRB1, -DRB3, -DRB4 and -DRB5) from 44 high-quality HPRC personal genome assemblies. For sequencing, we crafted HLA-specific probes and conducted capture-based targeted sequencing of the genomic DNA of the HPRC cohort, ensuring focused and comprehensive coverage of the HLA region of interest. We used publicly available short-read whole-genome sequencing (WGS) data from identical samples to offer a comparative perspective. To decipher the vast amount of sequencing data, we employed seven distinct software tools OptiType, HLA-VBseq, HISAT genotype, SpecHLA, T1K, QzType, and DRAGEN. Each tool offers unique capabilities and algorithms for HLA genotyping, allowing comprehensive analysis and validation of the results. We then compared these results with benchmarks derived from personal genome assemblies. Our findings present a comprehensive four-field-resolution HLA allele annotation for 44 HPRC samples. Significantly, our innovative targeted next-generation sequencing (NGS) approach for HLA genes showed superior accuracy compared with conventional short-read WGS. An integrated analysis involving QzType, T1K, and DRAGEN was developed, achieving 100% accuracy for all 11 HLA genes. In conclusion, our study highlighted the combination of targeted short-read sequencing and astute computational analysis as a robust approach for HLA genotyping. Furthermore, the HPRC cohort has emerged as a valuable assembly-based reference in this realm.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article