Using Nanopore Whole-Transcriptome Sequencing for Human Leukocyte Antigen Genotyping and Correlating Donor Human Leukocyte Antigen Expression with Flow Cytometric Crossmatch Results

Montgomery, Maureen C.; Liu, Chang; Petraroia, Rosanne; Weimer, Eric T.

doi:10.1016/j.jmoldx.2019.09.005

Cited by 18 publications

(25 citation statements)

References 46 publications

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“…Our results confirm the variability of expression among HLA class I alleles as previously reported [ 5 , 14 , 28 , 30 , 40 – 42 ]. Nevertheless, considering the mean expression of alleles at the locus level, our data are not in agreement with other publications classifying HLA-C mRNA expression as the lowest [ 30 , 43 ].…”

Section: Discussionsupporting

confidence: 92%

“…Intra- and inter-individual variation of HLA cell surface expression on T and B cells was also described to impact antibody dependent cytotoxic immune response [ 13 ]. More recently, HLA-expression was also shown to impact crossmatch outcomes in transplantation diagnostic [ 14 ]. Two retrospective clinical studies tested the impact of HLA expression on clinical outcome in the setting of HLA-C mismatched unrelated hematopoietic stem cell transplantation (HSCT).…”

Section: Introductionmentioning

confidence: 99%

“…[ 4 , 7 , 17 , 25 , 26 ]. The advent of more recent technologies using RNA sequencing has allowed qualitative, quantitative and equivalent inter-allelic expression analyses [ 14 , 27 – 30 ].…”

Section: Introductionmentioning

confidence: 99%

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Regulation of HLA class I expression by non-coding gene variations

et al. 2022

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The Human Leukocyte Antigen (HLA) is a critical genetic system for different outcomes after solid organ and hematopoietic cell transplantation. Its polymorphism is usually determined by molecular technologies at the DNA level. A potential role of HLA allelic expression remains under investigation in the context of the allogenic immune response between donors and recipients. In this study, we quantified the allelic expression of all three HLA class I loci (HLA-A, B and C) by RNA sequencing and conducted an analysis of expression quantitative traits loci (eQTL) to investigate whether HLA expression regulation could be associated with non-coding gene variations. HLA-B alleles exhibited the highest expression levels followed by HLA-C and HLA-A alleles. The max fold expression variation was observed for HLA-C alleles. The expression of HLA class I loci of distinct individuals demonstrated a coordinated and paired expression of both alleles of the same locus. Expression of conserved HLA-A~B~C haplotypes differed in distinct PBMC’s suggesting an individual regulated expression of both HLA class I alleles and haplotypes. Cytokines TNFα /IFNβ, which induced a very similar upregulation of HLA class I RNA and cell surface expression across alleles did not modify the individually coordinated expression at the three HLA class I loci. By identifying cis eQTLs for the HLA class I genes, we show that the non-coding eQTLs explain 29%, 13%, and 31% of the respective HLA-A, B, C expression variance in unstimulated cells, and 9%, 23%, and 50% of the variance in cytokine-stimulated cells. The eQTLs have significantly higher effect sizes in stimulated cells compared to unstimulated cells for HLA-B and HLA-C genes expression. Our data also suggest that the identified eQTLs are independent from the coding variation which defines HLA alleles and thus may be influential on intra-allele expression variability although they might not represent the causal eQTLs.

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Section: Discussionsupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

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Regulation of HLA class I expression by non-coding gene variations

et al. 2022

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“…Short read platforms are characterized by sequencing reads between 50 and 300 bp, while long-read platforms can sequence reads from 150 to >2 Mb ( Metzker, 2010 ; Jain et al, 2018 ). The application of long-read technology to HLA typing has been successfully demonstrated by several laboratories using DNA or RNA ( Liu et al, 2018a ; Liu, 20212018a; Lang et al, 2018 ; Montgomery et al, 2019 ; De Santis et al, 2020 ; Mosbruger et al, 2020 ). Long read technology is beneficial and applicable for HLA typing due to various advantages of the methodology, including shorter library preparation, real-time base calling, shorter sequencing times, and potential cost savings.…”

Section: Introductionmentioning

confidence: 99%

Unique Molecular Identifier-Based High-Resolution HLA Typing and Transcript Quantitation Using Long-Read Sequencing

et al. 2022

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HLA typing provides essential results for stem cell and solid organ transplants, as well as providing diagnostic benefits for various rheumatology, gastroenterology, neurology, and infectious diseases. It is becoming increasingly clear that understanding the expression of patient HLA transcripts can provide additional benefits for many of these same patient groups. Our study cohort was evaluated using a long-read RNA sequencing methodology to provide rapid HLA genotyping results and normalized HLA transcript expression. Our assay used NGSEngine to determine the HLA genotyping result and normalized mRNA transcript expression using Athlon2. The assay demonstrated an excellent concordance rate of 99.7%. Similar to previous studies, for the class I loci, patients demonstrated significantly lower expression of HLA-C than HLA-A and -B (Mann–Whitney U, p value = 0.0065 and p value = 0.0154, respectively). In general, the expression of class II transcripts was lower than that of class I transcripts. This study demonstrates a rapid high-resolution HLA typing assay using RNA-Seq that can provide accurate HLA genotyping and HLA allele-specific transcript expression in 7–8 h, a timeline short enough to perform the assay for deceased donors.

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“…ONT was also the first reported NGS HLA typing method tested for deceased donor allocation (De Santis et al, 2020). In addition to genomic sequencing data, ONT was used to genotype HLA class I loci and to determine their gene-level expression from RNA sequencing (RNA-Seq) reads (Montgomery et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Targeted RNA-Based Oxford Nanopore Sequencing for Typing 12 Classical HLA Genes

et al. 2021

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Identification of human leukocyte antigen (HLA) alleles from next-generation sequencing (NGS) data is challenging because of the high polymorphism and mosaic nature of HLA genes. Owing to the complex nature of HLA genes and consequent challenges in allele assignment, Oxford Nanopore Technologies’ (ONT) single-molecule sequencing technology has been of great interest due to its fitness for sequencing long reads. In addition to the read length, ONT’s advantages are its portability and possibility for a rapid real-time sequencing, which enables a simultaneous data analysis. Here, we describe a targeted RNA-based method for HLA typing using ONT sequencing and SeqNext-HLA SeqPilot software (JSI Medical Systems GmbH). Twelve classical HLA genes were enriched from cDNA of 50 individuals, barcoded, pooled, and sequenced in 10 MinION R9.4 SpotON flow cell runs producing over 30,000 reads per sample. Using barcoded 2D reads, SeqPilot assigned HLA alleles to two-field typing resolution or higher with the average read depth of 1750x. Sequence analysis resulted in 99–100% accuracy at low-resolution level (one-field) and in 74–100% accuracy at high-resolution level (two-field) with the expected alleles. There are still some limitations with ONT RNA sequencing, such as noisy reads, homopolymer errors, and the lack of robust algorithms, which interfere with confident allele assignment. These issues need to be inspected carefully in the future to improve the allele call rates. Nevertheless, here we show that sequencing of multiplexed cDNA amplicon libraries on ONT MinION can produce accurate high-resolution typing results of 12 classical HLA loci. For HLA research, ONT RNA sequencing is a promising method due to its capability to sequence full-length HLA transcripts. In addition to HLA genotyping, the technique could also be applied for simultaneous expression analysis.

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Using Nanopore Whole-Transcriptome Sequencing for Human Leukocyte Antigen Genotyping and Correlating Donor Human Leukocyte Antigen Expression with Flow Cytometric Crossmatch Results

Cited by 18 publications

References 46 publications

Regulation of HLA class I expression by non-coding gene variations

Regulation of HLA class I expression by non-coding gene variations

Unique Molecular Identifier-Based High-Resolution HLA Typing and Transcript Quantitation Using Long-Read Sequencing

Targeted RNA-Based Oxford Nanopore Sequencing for Typing 12 Classical HLA Genes

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