Derivation of HLA types from shotgun sequence datasets

René L Warren, Gina Choe, Douglas J Freeman, Mauro Castellarin, Sarah Munro, Richard Moore, Robert A Holt, René L Warren, Gina Choe, Douglas J Freeman, Mauro Castellarin, Sarah Munro, Richard Moore, Robert A Holt

Abstract

The human leukocyte antigen (HLA) is key to many aspects of human physiology and medicine. All current sequence-based HLA typing methodologies are targeted approaches requiring the amplification of specific HLA gene segments. Whole genome, exome and transcriptome shotgun sequencing can generate prodigious data but due to the complexity of HLA loci these data have not been immediately informative regarding HLA genotype. We describe HLAminer, a computational method for identifying HLA alleles directly from shotgun sequence datasets (http://www.bcgsc.ca/platform/bioinfo/software/hlaminer). This approach circumvents the additional time and cost of generating HLA-specific data and capitalizes on the increasing accessibility and affordability of massively parallel sequencing.

Figures

Figure 1
Figure 1
Computational predictions of HLA-I from shotgun data by targeted assembly (left) or read alignment (right). For targeted assembly, NGS reads having their first fifteen 5' bases matching one of HLA CDS (RNA-Seq) or genomic (WGS/exon capture) sequences are recruited and assembled de novo with TASR. Resulting sequence contigs are aligned against a database sequence of all predicted HLA CDS (RNA-Seq) or genomic sequences (WGS/exon capture), tracking best HLA hit(s). Reciprocal best alignments are considered in the same manner. Putative allele assignments from shotgun datasets (HLAminer) are informed by contig length, depth of coverage and similarity to reference sequences, when applicable. The probability of each prediction being correct is estimated by determining the probability of that prediction being observed by chance.
Figure 2
Figure 2
HLAminer performance. HLA allele group and protein coding allele predictions derived from targeted read assembly (black symbols) or direct read alignment (grey symbols) of simulated 100-nucleotide RNA-Seq, WGS and exon capture (ExCap) datasets were compared to original, spiked-in, HLA sequences and performance metrics evaluated (ambiguity, sensitivity and specificity represented by circle, triangle and square symbols, respectively). HLAminer predictions were also obtained from targeted assembly of colorectal cancer (CRC; blue symbols), lymphoma (DLBCL; red, orange and yellow symbols), 1000 Genomes (1KG; green symbols) and ovarian cancer (OV; violet and magenta symbols) patient tumor (T) and/or matched normal (N) shotgun datasets and compared to PCR-based HLA types to calculate performance metrics.

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