Distribution of HLA epitope frequencies in Turkish population

Objectives The antibodies interact with the “Human Leukocyte Antigen (HLA) antigens” at specific epitopes. “Epitopes” are present on a single HLA or shared by multiple antigens. In this study, we aim to determine the frequency of prevalent epitopes common in the Turkish population. Methods Non-related 644 healthy volunteers were recruited, and The “HLA-A, -B, -C, -DR -DQ’s” were typed using the “Next Generation Sequencing”. The provisional and confirmed epitopes were identified using the “HLA Epitope Registry databases, HLA Epitopia Maps and Immucor Epitope databases” dated 07.02.2018. Epitope frequencies were calculated by counting the shared epitopes in the total number of shared HLA Class epitopes in our sample database. Results Class I HLA’s had 298 epitopes that repeated a total of 158,117 times with frequencies ranging between 0.0006 and 2.03%, and the most frequent epitope was 170RY found on 119 different alleles. Class II HLA’s had 193 epitopes that repeated a total of 93,082 times with frequencies ranging between 0.002 and 1.36%, and the most frequent epitope was 108P found on 42 different alleles. Conclusions Our findings summarize both the provisional, and confirmed epitope frequencies in the Turkish population and may help clinicians and immunogeneticists develop a better understanding of HLA epitope mismatches.

Analysis of genetic variants in myeloproliferative neoplasms using a 22-gene next-generation sequencing panel

Background The Philadelphia (Ph)-negative myeloproliferative neoplasms (MPNs), namely essential thrombocythaemia (ET), polycythaemia vera (PV) and primary myelofibrosis (PMF), are a group of chronic clonal haematopoietic disorders that have the propensity to advance into bone marrow failure or acute myeloid leukaemia; often resulting in fatality. Although driver mutations have been identified in these MPNs, subtype-specific markers of the disease have yet to be discovered. Next-generation sequencing (NGS) technology can potentially improve the clinical management of MPNs by allowing for the simultaneous screening of many disease-associated genes. Methods The performance of a custom, in-house designed 22-gene NGS panel was technically validated using reference standards across two independent replicate runs. The panel was subsequently used to screen a total of 10 clinical MPN samples (ET n = 3, PV n = 3, PMF n = 4). The resulting NGS data was then analysed via a bioinformatics pipeline. Results The custom NGS panel had a detection limit of 1% variant allele frequency (VAF). A total of 20 unique variants with VAFs above 5% (4 of which were putatively novel variants with potential biological significance) and one pathogenic variant with a VAF of between 1 and 5% were identified across all of the clinical MPN samples. All single nucleotide variants with VAFs ≥ 15% were confirmed via Sanger sequencing. Conclusions The high fidelity of the NGS analysis and the identification of known and novel variants in this study cohort support its potential clinical utility in the management of MPNs. However, further optimisation is needed to avoid false negatives in regions with low sequencing coverage, especially for the detection of driver mutations in MPL.

ECCsplorer: a pipeline to detect extrachromosomal circular DNA (eccDNA) from next-generation sequencing data

Background Extrachromosomal circular DNAs (eccDNAs) are ring-like DNA structures physically separated from the chromosomes with 100 bp to several megabasepairs in size. Apart from carrying tandemly repeated DNA, eccDNAs may also harbor extra copies of genes or recently activated transposable elements. As eccDNAs occur in all eukaryotes investigated so far and likely play roles in stress, cancer, and aging, they have been prime targets in recent research—with their investigation limited by the scarcity of computational tools. Results Here, we present the ECCsplorer, a bioinformatics pipeline to detect eccDNAs in any kind of organism or tissue using next-generation sequencing techniques. Following Illumina-sequencing of amplified circular DNA (circSeq), the ECCsplorer enables an easy and automated discovery of eccDNA candidates. The data analysis encompasses two major procedures: first, read mapping to the reference genome allows the detection of informative read distributions including high coverage, discordant mapping, and split reads. Second, reference-free comparison of read clusters from amplified eccDNA against control sample data reveals specifically enriched DNA circles. Both software parts can be run separately or jointly, depending on the individual aim or data availability. To illustrate the wide applicability of our approach, we analyzed semi-artificial and published circSeq data from the model organisms Homo sapiens and Arabidopsis thaliana, and generated circSeq reads from the non-model crop plant Beta vulgaris. We clearly identified eccDNA candidates from all datasets, with and without reference genomes. The ECCsplorer pipeline specifically detected mitochondrial mini-circles and retrotransposon activation, showcasing the ECCsplorer’s sensitivity and specificity. Conclusion The ECCsplorer (available online at https://github.com/crimBubble/ECCsplorer) is a bioinformatics pipeline to detect eccDNAs in any kind of organism or tissue using next-generation sequencing data. The derived eccDNA targets are valuable for a wide range of downstream investigations—from analysis of cancer-related eccDNAs over organelle genomics to identification of active transposable elements.

Analysis Comparison for Rapid Identification of Pathogenic Virus from Infected Tissue Samples

When examining infectious samples, rapid identification of the pathogenic agent is required for diagnosis and treatment or for investigating the cause of death. In our previous study, we applied exhaustive amplification using non-specific primers (the rapid determination system of viral genome sequences, the RDV method) to identify the causative virus via swab samples from a cat with a suspected viral infection. The purpose of the current study is to investigate suitable methods for the rapid identification of causative pathogens from infected tissue samples. First, the influenza virus was inoculated into mice to prepare infected tissue samples. RNA extracted from the mouse lung homogenates was transcribed into cDNA and then analyzed using the RDV method and next-generation sequencing, using MiSeq and MinION sequencers. The RDV method was unable to detect the influenza virus in the infected tissue samples. However, influenza virus reads were detected using next-generation sequencing. Comparing MiSeq and MinION, the time required for library and sequence preparation was shorter for MinION sequencing than for MiSeq sequencing. We conclude that when a causative virus needs to be rapidly identified from an infectious sample, MinION sequencing is currently the method of choice.

Case Report: Metagenomic Next-Generation Sequencing for Diagnosis of Human Encephalitis and Endophthalmitis Caused by Pseudorabies Virus

PurposeThe objective of our study was to report a case of encephalitis and endophthalmitis caused by pseudorabies virus (PRV), identified using metagenomic next-generation sequencing (mNGS).Case PresentationA 54-year-old worker, from a swine slaughterhouse, developed signs of severe encephalitis, including fever, disturbance of consciousness, hypopnea, and status epilepticus, after finger injury at work. The PRV sequences were successfully identified from the blood, cerebrospinal fluid (CSF), and aqueous humor of the patient through mNGS, which was further verified using a Sanger sequencing.ConclusionOur case emphasizes the importance of mNGS in early diagnoses of infectious diseases, and gives a clue that PRV can spread across species and infect human. It is necessary to carry out a skin protection and education about disease prevention for people who have close contact with swine.