Clustering and alignment of polymorphic sequences for HLA-DRB1 genotyping

Area of Science:

• Immunogenetics
• Genomic Medicine
• Bioinformatics

Background:

• Human leukocyte antigen (HLA) genes on Chromosome 6p21 are highly polymorphic.
• HLA alleles are associated with various phenotypes, including narcolepsy, autoimmunity, and infectious disease responses.
• High-resolution HLA genotyping is critical for allogeneic transplant survival and understanding disease risk.

Purpose of the Study:

• To develop and validate a novel computational method for high-resolution HLA genotyping.
• To analyze HLA-DRB1 alleles in a cohort of ulcerative colitis patients.
• To improve the accuracy and efficiency of HLA genotyping from next-generation sequencing data.

Main Methods:

• Genomic DNA from 383 ulcerative colitis patients was analyzed for HLA-DRB1.
• HLA genotyping was performed using sequence-specific oligonucleotide probes and next-generation sequencing (Roche/454 GSFLX).
• The Clustering and Alignment of Polymorphic Sequences (CAPSeq) software was developed, utilizing MUMmer for sequence alignment and the R package diffusionMap for classification, incorporating Bootstrap Aggregating (Bagging) for enhanced accuracy.

Main Results:

• The CAPSeq software successfully generated 6-digit HLA sequence-specific genotype information from next-generation sequencing data.
• Incorporation of Bagging with 60 iterations improved genotyping accuracy.
• CAPSeq demonstrated high concordance (99.1%, 759/766 alleles) when compared to 4-digit genotypes obtained via sequence-specific oligonucleotide probes.

Conclusions:

• CAPSeq is an accurate and reliable method for high-resolution HLA-DRB1 genotyping using next-generation sequencing data.
• This method facilitates a deeper understanding of the contribution of specific HLA alleles to human health and disease.
• The developed software aids in advancing immunogenetic research and clinical applications, such as transplantation and disease association studies.