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July 7, 2019  |  

iMGEins: detecting novel mobile genetic elements inserted in individual genomes.

Recent advances in sequencing technology have allowed us to investigate personal genomes to find structural variations, which have been studied extensively to identify their association with the physiology of diseases such as cancer. In particular, mobile genetic elements (MGEs) are one of the major constituents of the human genomes, and cause genome instability by insertion, mutation, and rearrangement.We have developed a new program, iMGEins, to identify such novel MGEs by using sequencing reads of individual genomes, and to explore the breakpoints with the supporting reads and MGEs detected. iMGEins is the first MGE detection program that integrates three algorithmic components: discordant read-pair mapping, split-read mapping, and insertion sequence assembly. Our evaluation results showed its outstanding performance in detecting novel MGEs from simulated genomes, as well as real personal genomes. In detail, the average recall and precision rates of iMGEins are 96.67 and 100%, respectively, which are the highest among the programs compared. In the testing with real human genomes of the NA12878 sample, iMGEins shows the highest accuracy in detecting MGEs within 20?bp proximity of the breakpoints annotated.In order to study the dynamics of MGEs in individual genomes, iMGEins was developed to accurately detect breakpoints and report inserted MGEs. Compared with other programs, iMGEins has valuable features of identifying novel MGEs and assembling the MGEs inserted.


July 7, 2019  |  

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.


July 7, 2019  |  

Alignment-free genome comparison enables accurate geographic sourcing of white oak DNA.

The application of genomic data and bioinformatics for the identification of restricted or illegally-sourced natural products is urgently needed. The taxonomic identity and geographic provenance of raw and processed materials have implications in sustainable-use commercial practices, and relevance to the enforcement of laws that regulate or restrict illegally harvested materials, such as timber. Improvements in genomics make it possible to capture and sequence partial-to-complete genomes from challenging tissues, such as wood and wood products.In this paper, we report the success of an alignment-free genome comparison method, [Formula: see text] that differentiates different geographic sources of white oak (Quercus) species with a high level of accuracy with very small amount of genomic data. The method is robust to sequencing errors, different sequencing laboratories and sequencing platforms.This method offers an approach based on genome-scale data, rather than panels of pre-selected markers for specific taxa. The method provides a generalizable platform for the identification and sourcing of materials using a unified next generation sequencing and analysis framework.


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