High-throughput Interpretation of Killer-cell Immunoglobulin-like Receptor Short-read Sequencing Data with PING.

The killer-cell immunoglobulin-like receptor (KIR) complex on chromosome 19 encodes receptors that modulate the activity of natural killer cells, and variation in these genes has been linked to infectious and autoimmune disease, as well as having bearing on pregnancy and transplant outcomes. The medical relevance and high variability of KIR genes makes short-read sequencing an attractive technology for interrogating the region, providing a high-throughput, high-fidelity sequencing method that is cost-effective. However, because this gene complex is characterized by extensive nucleotide polymorphism, structural variation including gene fusions and deletions, and a high level of homology between genes, its interrogation at high resolution has been thwarted by bioinformatic challenges, with most studies limited to examining presence or absence of specific genes. Here, we present the PING (Pushing Immunogenetics to the Next Generation) pipeline, which incorporates empirical data, novel alignment strategies and a custom alignment processing workflow to enable high-throughput KIR sequence analysis from short-read data. PING provides KIR gene copy number classification functionality for all KIR genes through use of a comprehensive alignment reference. The gene copy number determined per individual enables an innovative genotype determination workflow using genotype-matched references. Together, these methods address the challenges imposed by the structural complexity and overall homology of the KIR complex. To determine copy number and genotype determination accuracy, we applied PING to European and African validation cohorts and a synthetic dataset. PING demonstrated exceptional copy number determination performance across all datasets and robust genotype determination performance. Finally, an investigation into discordant genotypes for the synthetic dataset provides insight into misaligned reads, advancing our understanding in interpretation of short-read sequencing data in complex genomic regions. PING promises to support a new era of studies of KIR polymorphism, delivering high-resolution KIR genotypes that are highly accurate, enabling high-quality, high-throughput KIR genotyping for disease and population studies.

Allele-Level KIR Genotyping of More Than a Million Samples: Workflow, Algorithm, and Observations.

The killer-cell immunoglobulin-like receptor (KIR) genes regulate natural killer cell activity, influencing predisposition to immune mediated disease, and affecting hematopoietic stem cell transplantation (HSCT) outcome. Owing to the complexity of the KIR locus, with extensive gene copy number variation (CNV) and allelic diversity, high-resolution characterization of KIR has so far been applied only to relatively small cohorts. Here, we present a comprehensive high-throughput KIR genotyping approach based on next generation sequencing. Through PCR amplification of specific exons, our approach delivers both copy numbers of the individual genes and allelic information for every KIR gene. Ten-fold replicate analysis of a set of 190 samples revealed a precision of 99.9%. Genotyping of an independent set of 360 samples resulted in an accuracy of more than 99% taking into account consistent copy number prediction. We applied the workflow to genotype 1.8 million stem cell donor registry samples. We report on the observed KIR allele diversity and relative abundance of alleles based on a subset of more than 300,000 samples. Furthermore, we identified more than 2,000 previously unreported KIR variants repeatedly in independent samples, underscoring the large diversity of the KIR region that awaits discovery. This cost-efficient high-resolution KIR genotyping approach is now applied to samples of volunteers registering as potential donors for HSCT. This will facilitate the utilization of KIR as additional selection criterion to improve unrelated donor stem cell transplantation outcome. In addition, the approach may serve studies requiring high-resolution KIR genotyping, like population genetics and disease association studies.

The double mutation L109M and R448M of HIV-1 reverse transcriptase decreases fidelity of DNA synthesis by promoting mismatch elongation.

Changes of Leu109 and Arg448 of human immunodeficiency virus type 1 (HIV-1) reverse transcriptase (RT) have as yet not been associated with altered fitness. However, in a recent study, we described that the simultaneous substitution of L109 and R448 by methionine leads to an error-producing polymerase phenotype that is not observed for the isolated substitutions. The double mutant increased the error rate of DNA-dependent DNA synthesis 3.1-fold as compared to the wildtype enzyme and showed a mutational spectrum with a fraction of 28% frameshift mutations and 48% transitions. We show here that weaker binding of DNA:DNA primer-templates as indicated by an increased dissociation rate constant (koff) could account for the higher frameshift error rate. Furthermore, we were able to explain the prevalence of transition mutations with the finding that HIV-1 RT variant L109M/R448M preferred misincorporation of C opposite A and elongation of C:A mismatches.

Activity-based selection of HIV-1 reverse transcriptase variants with decreased polymerization fidelity.

HIV-1 reverse transcriptase (HIV-1 RT) copies the RNA genome of HIV-1 into DNA, thereby committing errors at an exceptionally high frequency. Viral offspring evolve rapidly and consequently are capable of evading the immune response as well as antiviral treatment. However, error-prone viral replication could drive HIV close to extinction owing to an intolerable load of deleterious mutations. We applied a genetic selection scheme to identify variants of HIV-1 RT with a further increased error rate to study the relationship between error rate and viral replication. Using this approach, we identified 16 mutator candidates, two of which were purified and further studied in vitro. One of these variant enzymes showed a generally increased mutation frequency as compared with the reference enzyme. A single amino acid residue, R448, is probably responsible for the observed effect. Mutation of this residue, which is located within the RNase H domain of HIV-1 RT, seems to perturb the interaction with template RNA and consequently affects polymerase activity and fidelity.