Group-specific amplification of HLA-DQA1 revealed a number of genomic full-length sequences including the novel HLA alleles DQA1*01:10 and DQA1*01:11

HLA class II peptide-binding-region analysis reveals funneling of polymorphism in action

BACKGROUND

HLA-class II proteins hold important roles in key physiological processes. The purpose of this study was to compile all class II alleles reported in human population and investigate patterns in pocket variants and their combinations, focusing on the peptide-binding region (PBR).

METHODS

For this purpose, all protein sequences of DPA1, DQA1, DPB1, DQB1 and DRB1 were selected and filtered, in order to have full PBR sequences. Proportional representation was used for pocket variants while population data were also used.

RESULTS

All pocket variants and PBR sequences were retrieved and analyzed based on the preference of amino acids and their properties in all pocket positions. The observed number of pocket variants combinations was much lower than the possible inferred, suggesting that PBR formation is under strict funneling. Also, although class II proteins are very polymorphic, in the majority of the reported alleles in all populations, a significantly less polymorphic pocket core was found.

CONCLUSIONS

Pocket variability of five HLA class II proteins was studied revealing favorable properties of each protein. The actual PBR sequences of HLA class II proteins appear to be governed by restrictions that lead to the establishment of only a fraction of the possible combinations and the polymorphism recorded is the result of intense funneling based on function.

Questionable expression of unstable DQ heterodimer containing HLA-DQA1*01:07

Human leukocyte antigens (HLA)-DQA1*01:07 was identified as an HLA-DQ blank specificity that segregated with the serological HLA-A2, -B7, -DR14, -DR52 haplotype, which carried DQB1*05:03. The blank specificity of DQA1*01:07-DQB1*05:03 may be because of lack of reactivity of available typing sera, or disruption of proper assembly of DQ heterodimer. The cDNA sequence of DQA1*01:07 is nearly identical to DQA1*01:04 except for a variant at position 304, which results in the replacement of an arginine with a cysteine at 79α. To determine whether the DQA1*01:07 product can be expressed on cell-surface, we co-expressed DQA1*01:07 with various DQB1*05 or *06 alleles in fibroblast cells. Cell-surface expression of DQ was detectable when DQA1*01:07 was co-expressed with DQB1*06:04 but undetectable with other DQB1*05 and DQB1*06 alleles, including DQB1*05:03, to which DQA1*01:07 was encoded in cis. These data suggest that DQA1*01:07 may act as a phenotypically null allele in the DQA1*01:07-DQB1*05:03 haplotype, while it can be expressed at a low level in the presences of certain DQB1*06 alleles, such as DQB1*06:04, in trans. Based on the null or low expression of DQA1*01:07 as shown in the previous and present studies, DQA1*01:07 has recently been renamed to DQA1*01:07Q, indicating its questionable expression.

Minimum information for reporting next generation sequence genotyping (MIRING): Guidelines for reporting HLA and KIR genotyping via next generation sequencing

The development of next-generation sequencing (NGS) technologies for HLA and KIR genotyping is rapidly advancing knowledge of genetic variation of these highly polymorphic loci. NGS genotyping is poised to replace older methods for clinical use, but standard methods for reporting and exchanging these new, high quality genotype data are needed. The Immunogenomic NGS Consortium, a broad collaboration of histocompatibility and immunogenetics clinicians, researchers, instrument manufacturers and software developers, has developed the Minimum Information for Reporting Immunogenomic NGS Genotyping (MIRING) reporting guidelines. MIRING is a checklist that specifies the content of NGS genotyping results as well as a set of messaging guidelines for reporting the results. A MIRING message includes five categories of structured information - message annotation, reference context, full genotype, consensus sequence and novel polymorphism - and references to three categories of accessory information - NGS platform documentation, read processing documentation and primary data. These eight categories of information ensure the long-term portability and broad application of this NGS data for all current histocompatibility and immunogenetics use cases. In addition, MIRING can be extended to allow the reporting of genotype data generated using pre-NGS technologies. Because genotyping results reported using MIRING are easily updated in accordance with reference and nomenclature databases, MIRING represents a bold departure from previous methods of reporting HLA and KIR genotyping results, which have provided static and less-portable data. More information about MIRING can be found online at miring.immunogenomics.org.

The use of haplotype-specific transcripts improves sample annotation consistency

Background

Exact sample annotation in expression microarray datasets is essential for any type of pharmacogenomics research.

Results

Candidate markers were explored through the application of Hartigans’ dip test statistics to a publically available human whole genome microarray dataset. The marker performance was tested on 188 serial samples from 53 donors and of variable tissue origin from five public microarray datasets. A qualified transcript marker panel consisting of three probe sets for human leukocyte antigens HLA-DQA1 (2 probe sets) and HLA-DRB4 identified sample donor identifier inconsistencies in six of the 188 test samples. About 3% of the test samples require root-cause analysis due to unresolvable inaccuracies.

Conclusions

The transcript marker panel consisting of HLA-DQA1 and HLA-DRB4 represents a robust, tissue-independent composite marker to assist control donor annotation concordance at the transcript level. Allele-selectivity of HLA genes renders them good candidates for “fingerprinting” with donor specific expression pattern.