Posttranscriptional Regulation of HLA-A Protein Expression by Alternative Polyadenylation Signals Involving the RNA-Binding Protein Syncrip

Kulkarni, S. R.; Ramsuran, Veron; Ručević, Marijana; Singh, Sukhvinder; Lied, Alexandra; Kulkarni, Viraj; Ó'hUigín, Colm; Gall, Sylvie Le; Carrington, Mary

doi:10.4049/jimmunol.1700697

Cited by 25 publications

(19 citation statements)

References 68 publications

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“…HLA-A and HLA-DPA1 both show differentially expressed isoforms with alternative polyA sites. While the alternative HLA-A isoform was previously observed 35,36 , the HLA-DPA1 isoform was not ( Fig. 3C,D).…”

Section: Allele Specific Isoform Expressionmentioning

confidence: 48%

Complete characterization of the human immune cell transcriptome using accurate full-length cDNA sequencing

Cole

Byrne

Adams

et al. 2019

Preprint

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ABSTRACTThe human immune system relies on highly complex and diverse transcripts and the proteins they encode. These include transcripts for Human Leukocyte Antigen (HLA) class I and II receptors which are essential for self/non-self discrimination by the immune system as well as transcripts encoding B cell and T cell receptors (BCR and TCR) which recognize, bind, and help eliminate foreign antigens.HLA genes are highly diverse within the human population with each individual possessing two of thousands of different alleles in each of the 9 major HLA genes. Determining which combination of alleles an individual possesses for each HLA gene (high-resolution HLA-typing) is essential to establish donor-recipient compatibility in organ and bone-marrow transplantations. BCR and TCR genes in turn are generated by recombining a diverse set of gene segments on the DNA level in each maturing B and T cell, respectively. This process generates adaptive immune receptor repertoires (AIRR) of composed of unique transcripts expressed by each B and T cells. These repertoires carry a vast amount of health relevant information. Both short-read RNA-seq based HLA-typing1 and adaptive immune receptor repertoire sequencing2–5 currently rely heavily on our incomplete knowledge of the genetic diversity at HLA6 and BCR/TCR loci7,8.Here we used our nanopore sequencing based Rolling Circle toConcatemeric Consensus (R2C2) protocol9 to generate over 10,000,000 full-length cDNA sequences at a median accuracy of 97.9%. We used this dataset to demonstrate that deep and accurate full-length cDNA sequencing can - in addition to providing isoform-level transcriptome analysis for over 9,000 loci - be used to generate accurate sequences of HLA alleles for HLA allele typing and discovery as well as detailed AIRR data for the analysis of the adaptive immune system without requiring specific knowledge of the diversity at HLA and BCR/TCR loci.

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Section: Allele Specific Isoform Expressionmentioning

confidence: 48%

Complete characterization of the human immune cell transcriptome using accurate full-length cDNA sequencing

Cole

Byrne

Adams

et al. 2019

Preprint

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“…Up to 70% of human genes use alternative polyadenylation sites (PAS) at the 3′ end of the gene to create a longer or shorter product, with immune genes in particular switching to the shorter form on infection and upregulation (Kulkarni et al, ). Variation in HLA‐A expression has been shown to be dependent on two such PAS, the nearer being conserved but the more distant is disrupted by sequence variation in some alleles.…”

Section: Factors Affecting Surface Expressionmentioning

confidence: 99%

“…In resting cells, HLA‐A*03 uses the distal PAS resulting in lower expression, but switches to the proximal PAS on upregulation by some pathogens, enabling greater surface expression of the protein and increased presentation of pathogenic peptides. HLA‐A*01 and A*11 are only able to utilize the proximal PAS and do not switch to the resultant low expression PAS when not activated (Kulkarni et al, ). This alternate PAS usage does not occur for HLA‐B and HLA‐C which only possess the more conserved distal polyadenylation site, suggesting that HLA‐A upregulation is more greatly influenced by infection or other stimulation.…”

Section: Factors Affecting Surface Expressionmentioning

confidence: 99%

Factors affecting HLA expression: A review

Carey

Poulton

Poles

2019

Int J Immunogenetics

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The detection and semiquantitative measurement of circulating human leucocyte antigen (HLA)‐specific antibodies is essential for the management of patients before and after transplantation. In addition, the pretransplant cross‐match to assess the reactivity of recipient HLA antibody against donor lymphocytes has long been the gold standard to prevent hyperacute rejection. Whilst both of these tests assume that recipient HLA‐specific antibody is the only variable in the assessment of transplant risk, this is not the case. Transplant immunologists recognize that some HLA antigens are expressed at levels a magnitude lower than others (e.g., HLA‐C, HLA‐DQ), but within loci, and between different cell types there are many factors that influence HLA expression in both resting and activated cells. HLA is not usually expressed without the specific promoter proteins NLRC5, for HLA class I, and CIITA, for class II. The quantity of HLA protein production is then affected by factors including promoter region polymorphisms, alternative exon splice sites, methylation and microRNA‐directed degradation. Different loci are influenced by multiple combinations of these control mechanisms making prediction of HLA regulation difficult, but an ability to measure the cellular expression of each HLA antigen, in conjunction with knowledge of circulating HLA‐specific antibody, would lead to a more informed algorithm to assess transplant risk.

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“…The mechanisms underlying the above-mentioned associations between SNP variation and HLA expression are only partly elucidated. For HLA-A, they have been suggested to be correlated with differential methylation and/or the usage of different polyadenylation sites (PAS) ( 2 , 3 ). For HLA-C and HLA-DPB1, no specific mechanisms for the observed genetic control of expression levels have been postulated to date.…”

Section: Introductionmentioning

confidence: 99%

Dissecting Genetic Control of HLA-DPB1 Expression and Its Relation to Structural Mismatch Models in Hematopoietic Stem Cell Transplantation

et al. 2018

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HLA expression levels have been suggested to be genetically controlled by single nucleotide polymorphisms (SNP) in the untranslated regions (UTR), and expression variants have been associated with the outcome of chronic viral infection and hematopoietic stem cell transplantation (HSCT). In particular, the 3′UTR rs9277534-G/A SNP in HLA-DPB1 has been associated with graft-versus-host-disease after HSCT (Expression model); however its relevance in different immune cells and its mode of action have not been systematically addressed. In addition, there is a strong though not complete overlap between the rs9277534-G/A SNP and structural HLA-DPB1 T cell epitope (TCE) groups which have also been associated with HSCT outcome (TCE Structural model). Here we confirm and extend previous findings of significantly higher HLA-DPB1 expression in B cell lines, unstimulated primary B cells, and monocytes homozygous for rs9277534-G compared to those homozygous for rs9277534-A. However, these differences were abrogated by interferon-γ stimulation or differentiation into dendritic cells. We identify at least seven 3′UTR rs9277534-G/A haplotypes differing by a total of 37 SNP, also characterized by linkage to length variants of a short tandem repeat (STR) in intron 2 and TCE group assignment. 3′UTR mapping did not show any significant differences in post-transcriptional regulation assessed by luciferase assays between two representative rs9277534-G/A haplotypes for any of eight overlapping fragments. Moreover, no evidence for alternative splicing associated with the intron 2 STR was obtained by RT-PCR. In an exemplary cohort of 379 HLA-DPB1 mismatched donor-recipient pairs, risk prediction by the Expression model and the Structural TCE model was 36.7% concordant, with the majority of discordances due to non-applicability of the Expression model. HLA-DPB1 from different TCE groups expressed in the absence of the 3′UTR at similar levels by transfected HeLa cells elicited significantly different mean alloreactive CD4+ T-cell responses, as assessed by CD137 upregulation assays in 178 independent cultures. Taken together, our data provide new insights into the cell type-specific and mechanistic basis of the association between the rs9277534-G/A SNP and HLA-DPB1 expression, and show that, despite partial overlap between both models in HSCT risk-prediction, differential alloreactivity determined by the TCE structural model occurs independently from HLA-DPB1 differential expression.

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Posttranscriptional Regulation of HLA-A Protein Expression by Alternative Polyadenylation Signals Involving the RNA-Binding Protein Syncrip

Cited by 25 publications

References 68 publications

Complete characterization of the human immune cell transcriptome using accurate full-length cDNA sequencing

Complete characterization of the human immune cell transcriptome using accurate full-length cDNA sequencing

Factors affecting HLA expression: A review

Dissecting Genetic Control of HLA-DPB1 Expression and Its Relation to Structural Mismatch Models in Hematopoietic Stem Cell Transplantation

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