Human Leukocyte Antigen Typing by Next-Generation Sequencing

2018 ◽  
Vol 38 (4) ◽  
pp. 565-578 ◽  
Author(s):  
Tracie Profaizer ◽  
Attila Kumánovics
Keyword(s):  
Next Generation Sequencing ◽  
Human Leukocyte Antigen ◽  
Human Leukocyte ◽  
Next Generation ◽  
Human Leukocyte Antigen Typing ◽  
Leukocyte Antigen ◽  
Generation Sequencing

scholarly journals A New Human Leukocyte Antigen Typing Algorithm Combined With Currently Available Genotyping Tools Based on Next-Generation Sequencing Data and Guidelines to Select the Most Likely Human Leukocyte Antigen Genotype

2021 ◽  
Vol 12 ◽  
Author(s):  
Miseon Lee ◽  
Jeong-Han Seo ◽  
Sungjae Song ◽  
In Hye Song ◽  
Su Yeon Kim ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Human Leukocyte Antigen ◽  
Human Leukocyte ◽  
Next Generation Sequencing Data ◽  
Next Generation ◽  
Leukocyte Antigen ◽  
Hla Type ◽  
Hla Genotyping ◽  
Ngs Data ◽  
Generation Sequencing

BackgroundHigh-precision human leukocyte antigen (HLA) genotyping is crucial for anti-cancer immunotherapy, but existing tools predicting HLA genotypes using next-generation sequencing (NGS) data are insufficiently accurate.Materials and MethodsWe compared availability, accuracy, correction score, and complementary ratio of eight HLA genotyping tools (OptiType, HLA-HD, PHLAT, seq2HLA, arcasHLA, HLAscan, HLA*LA, and Kourami) using 1,005 cases from the 1000 Genomes Project data. We created a new HLA-genotyping algorithm combining tools based on the precision and the accuracy of tools’ combinations. Then, we assessed the new algorithm’s performance in 39 in-house samples with normal whole-exome sequencing (WES) data and polymerase chain reaction–sequencing-based typing (PCR-SBT) results.ResultsRegardless of the type of tool, the calls presented by more than six tools concordantly showed high accuracy and precision. The accuracy of the group with at least six concordant calls was 100% (97/97) in HLA-A, 98.2% (112/114) in HLA-B, 97.3% (142/146) in HLA-C. The precision of the group with at least six concordant calls was over 98% in HLA-ABC. We additionally calculated the accuracy of the combination tools considering the complementary ratio of each tool and the accuracy of each tool, and the accuracy was over 98% in all groups with six or more concordant calls. We created a new algorithm that matches the above results. It was to select the HLA type if more than six out of eight tools presented a matched type. Otherwise, determine the HLA type experimentally through PCR-SBT. When we applied the new algorithm to 39 in-house cases, there were more than six matching calls in all HLA-A, B, and C, and the accuracy of these concordant calls was 100%.ConclusionsHLA genotyping accuracy using NGS data could be increased by combining the current HLA genotyping tools. This new algorithm could also be useful for preliminary screening to decide whether to perform an additional PCR-based experimental method instead of using tools with NGS data.

scholarly journals Relationship between obstructive sleep apnea and human leukocyte antigen variants

2021 ◽  
Author(s):  
Ayse Gul Zamani ◽  
Sebnem Yosunkaya ◽  
Adil Zamani ◽  
Hulya Vatansev ◽  
Ahmet Burak Arslan ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Next Generation Sequencing ◽  
Sleep Apnea ◽  
Human Leukocyte Antigen ◽  
Human Leukocyte ◽  
Turkish Population ◽  
Next Generation ◽  
Leukocyte Antigen ◽  
Obstructive Sleep ◽  
Generation Sequencing

Background and aim: The obstructive sleep apnea (OSA) is a common, complex and polygenic disease and it has high risk of serious complications. The human leukocyte antigen (HLA) system plays a crucial role in the regulation of immune function by discriminating self from non-self. In recent years there has been rapid advancement in "Next Generation Sequencing" technology. It enables the detection of HLA alleles in four or even six digits, providing a high level of precision. The aim of the present study was to investigate the genetic variants at HLA-A,-B,-C,-DQB1 and -DRB1 loci in OSA patients and unrelated healthy individuals by targeted NGS in the Turkish population. Materials methods: Fifty newly diagnosed patients with OSA and 50 control subjects were enrolled in the study. OSA diagnosis was made by utilizing the apnea-hypopnea index (AHI)≥5 in overnight polysomnography (PSG). Blood samples were obtained in the morning, after PSG. Controls were randomly selected from healthy volunteers who had a low risk for OSA. Genotyping of HLA-A, B, C, DRB1 and DQB1 genes were performed by using next generation sequencing. Results: HLA-A*02:01, HLA-C*03:03:01, HLA-C*14:03, HLA DRB1*04:05 alleles were found more frequently in OSA patients, but not in the controls (p=0.036, p=0.007, p=0.043 and 0.013, respectively). The allele frequencies of HLA-A*03:01 and HLA-B*35:02 were significantly higher in controls compared to OSA patients (p=0.024 and p=0.043). Conclusion: These results suggest that HLA-A*02:01, HLA-C*03:03:01, HLA-C*14:03, HLA DRB1*04:05 alleles may play a predisposing role in the Turkish population with OSA. In addition, HLA-A*03:01 and HLA-B*35:02 alleles may be protective in this population.

scholarly journals Distribution of HLA epitope frequencies in Turkish population

2022 ◽  
Vol 0 (0) ◽  
Author(s):  
Fatma Savran Oguz ◽  
Suleyman Rustu Oguz ◽  
Yeliz Ogret ◽  
Tanju Sedat Karadeniz ◽  
Hayriye Senturk Ciftci ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Human Leukocyte Antigen ◽  
Healthy Volunteers ◽  
Hla Antigens ◽  
Human Leukocyte ◽  
Turkish Population ◽  
Next Generation ◽  
Leukocyte Antigen ◽  
Shared Epitopes ◽  
Generation Sequencing

Abstract Objectives The antibodies interact with the “Human Leukocyte Antigen (HLA) antigens” at specific epitopes. “Epitopes” are present on a single HLA or shared by multiple antigens. In this study, we aim to determine the frequency of prevalent epitopes common in the Turkish population. Methods Non-related 644 healthy volunteers were recruited, and The “HLA-A, -B, -C, -DR -DQ’s” were typed using the “Next Generation Sequencing”. The provisional and confirmed epitopes were identified using the “HLA Epitope Registry databases, HLA Epitopia Maps and Immucor Epitope databases” dated 07.02.2018. Epitope frequencies were calculated by counting the shared epitopes in the total number of shared HLA Class epitopes in our sample database. Results Class I HLA’s had 298 epitopes that repeated a total of 158,117 times with frequencies ranging between 0.0006 and 2.03%, and the most frequent epitope was 170RY found on 119 different alleles. Class II HLA’s had 193 epitopes that repeated a total of 93,082 times with frequencies ranging between 0.002 and 1.36%, and the most frequent epitope was 108P found on 42 different alleles. Conclusions Our findings summarize both the provisional, and confirmed epitope frequencies in the Turkish population and may help clinicians and immunogeneticists develop a better understanding of HLA epitope mismatches.

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