Comparison between qPCR and RNA-seq reveals challenges of quantifying HLA expression
- 28 January 2023
- journal article
- research article
- Published by Springer Nature in Immunogenetics
- Vol. 75 (3) , 249-262
Abstract
Human leukocyte antigen (HLA) class I and II loci are essential elements of innate and acquired immunity. Their functions include antigen presentation to T cells leading to cellular and humoral immune responses, and modulation of NK cells. Their exceptional influence on disease outcome has now been made clear by genome-wide association studies. The exons encoding the peptide-binding groove have been the main focus for determining HLA effects on disease susceptibility/pathogenesis. However, HLA expression levels have also been implicated in disease outcome, adding another dimension to the extreme diversity of HLA that impacts variability in immune responses across individuals. To estimate HLA expression, immunogenetic studies traditionally rely on quantitative PCR (qPCR). Adoption of alternative high-throughput technologies such as RNA-seq has been hampered by technical issues due to the extreme polymorphism at HLA genes. Recently, however, multiple bioinformatic methods have been developed to accurately estimate HLA expression from RNA-seq data. This opens an exciting opportunity to quantify HLA expression in large datasets but also brings questions on whether RNA-seq results are comparable to those by qPCR. In this study, we analyze three classes of expression data for HLA class I genes for a matched set of individuals: (a) RNA-seq, (b) qPCR, and (c) cell surface HLA-C expression. We observed a moderate correlation between expression estimates from qPCR and RNA-seq for HLA-A, -B, and -C (0.2 ≤ rho ≤ 0.53). We discuss technical and biological factors which need to be accounted for when comparing quantifications for different molecular phenotypes or using different techniques.Keywords
Funding Information
- National Institute of General Medical Sciences (GM075091)
- Division of Intramural Research (AI157850)
- South African Medical Research Council
- SANTHE (DEL-15-006)
- Frederick National Laboratory for Cancer Research (HHSN261200800001E)
- Fundação de Amparo à Pesquisa do Estado de São Paulo (2012/18010-0, 2013/22007-7, 2014/12123-2, 2016/24734-1)
- Conselho Nacional de Desenvolvimento Científico e Tecnológico (470043/2014-8)
This publication has 75 references indexed in Scilit:
- Major Histocompatibility Complex Genomics and Human DiseaseAnnual Review of Genomics and Human Genetics, 2013
- The Genotype-Tissue Expression (GTEx) projectNature Genetics, 2013
- STAR: ultrafast universal RNA-seq alignerBioinformatics, 2012
- A Novel Variant Marking HLA-DP Expression Levels Predicts Recovery from Hepatitis B Virus InfectionJournal of Virology, 2012
- Multiple Sclerosis Risk Variant HLA-DRB1*1501 Associates with High Expression of DRB1 Gene in Different Human PopulationsPLOS ONE, 2012
- Differential microRNA regulation of HLA-C expression and its association with HIV controlNature, 2011
- NLR family member NLRC5 is a transcriptional regulator of MHC class I genesProceedings of the National Academy of Sciences, 2010
- HLA-C cell surface expression and control of HIV/AIDS correlate with a variant upstream of HLA-CNature Genetics, 2009
- The Yin and Yang of HLA and KIR in human diseaseSeminars in Immunology, 2008
- A high-resolution HLA and SNP haplotype map for disease association studies in the extended human MHCNature Genetics, 2006