In silicotools for accurate HLA and KIR inference from clinical sequencing data empower immunogenetics on individual-patient and population scales

Abstract

Immunogenetic variation in humans is important in research, clinical diagnosis and increasingly a target for therapeutic intervention. Two highly polymorphic loci play critical roles, namely the human leukocyte antigen (HLA) system, which is the human version of the major histocompatibility complex (MHC), and the Killer-cell immunoglobulin-like receptors (KIR) that are relevant for responses of Natural Killer (NK) cells and some subsets of T cells. Their accurate classification has typically required the use of dedicated biological specimens and a combination of in vitro and in silico efforts. Increased availability of next generation sequencing data has led to the development of ancillary computational solutions. Here, we report an evaluation of recently published algorithms to computationally infer complex immunogenetic variation in the form of HLA alleles and KIR haplotypes from whole-genome or whole-exome sequencing data. For both HLA allele and KIR gene typing, we identified tools that yielded >97% overall accuracy for 4-digit HLA types, and >99% overall accuracy for KIR gene presence, suggesting the readiness of in silico solutions for use in clinical and high-throughput research settings.

The Immunogenic Potential of Recurrent Cancer Drug Resistance Mutations: An In Silico Study

“…In particular, we ran the shell_call_hla_type script, with the following parameters: race = unknown, includeFreq = 1, and insertCalc = 0. Note that although POLYSOLVER was originally developed to run on whole exome sequencing data, benchmarking experiments indicate that it performs well also on WGS data at depth of sequencing 30x or higher ( 54 – 56 ).…”

HLA/MHC and KIR characterization in humans and non‐human primates using Oxford Nanopore Technologies and Pacific Biosciences sequencing platforms

“…[126][127][128][129] The extensive gene diversity and allele variation of MHC and KIR might require specialized computational tools for streamlined and accurate high-resolution characterization, as is also seen for HLA and KIR typing tools using short-read datasets. 130,131 Most of these conventional short-read tools are unable to cope with long reads and are therefore not applicable for PacBio and ONT data. So far, only a few specialized tools have been validated with long and noisy reads to type MHC alleles at high resolution, whereas similar tools for KIR allele calling are not reported yet.…”

“…The extensive gene diversity and allele variation of MHC and KIR might require specialized computational tools for streamlined and accurate high‐resolution characterization, as is also seen for HLA and KIR typing tools using short‐read datasets 130,131 . Most of these conventional short‐read tools are unable to cope with long reads and are therefore not applicable for PacBio and ONT data.…”

MiDAS - Meaningful Immunogenetic Data at Scale

“…2 The extreme amount of genetic variation has made it challenging to accurately characterize individuals' HLA and KIR genotypes, but besides dedicated typing methods, there are now multiple tools available for inference from next generation sequencing or single nucleotide polymorphism (SNP) array genotyping data at scale. [3][4][5] However, the availability of immunogenetic variation data is only the first necessary step in uncovering and understanding its role in immune-related traits, and statistical considerations are more complex when compared to the millions of common single nucleotide polymorphisms (SNPs) or copy number variants (CNVs) in our genomes that predominantly have two allelic states.…”