June 1, 2021  |  

HLA variant identification techniques

The Human Leukocyte Antigen (HLA) genes located on chromosome 6 are responsible for regulating immune function via antigen presentation and are one of the determining factors for stem cell and organ transplantation compatibility. Additionally various alleles within this region have been implicated in autoimmune disorders, cancer, vaccine response and both non-infectious and infectious disease risk. The HLA region is highly variable; containing repetitive regions; and co-dominantly expressed genes. This complicates short read mapping and means that assessing the effect of variation within a gene requires full phase information to resolve haplotypes.One solution to the problem of HLA identification is the use of statistical inference to suggest the most likely diploid alleles given the genotypes observed. The assumption of this approach is the availability of an extensive reference panel. Whilst there exists good population genetics data for imputing European populations, there remains a paucity of information about variation in African populations. Filling this gap is one of the aims of the Genome Diversity in Africa Project and as a first step we are performing a pilot study to identify the optimal method for determining HLA type information for large numbers of samples from African populations.To that end we have obtained samples from 125 consented African participants selected from 5 populations across Africa (Morrocan, Ashanti, Igbo, Kalenjin, and Zulu). The methods included in our pilot study are Sanger sequencing (ABI), NGS on HiSeqX Ten platform (Illumina); long-range PCR combined with single molecule real-time (SMRT) sequencing (PacBio); and for a subset of samples library preparation on GemCode Platform (10x Genomics), which delivers valuable long range contextual information, combined with Illumina NGS sequencing.Results from capillary sequencing suggests the presence of a minimum of two novel alleles. Long Range PCR have been performed initially on a subset of samples using both primers sourced from GenDX and designed as described in Shiina et al (2012). Initial results from both primer sets were promising on Promega DNA test samples but only the GenDX primers proved effective on the African samples, producing consistently PCR products of the expected size in the Igbo, Ashanti, Morrocan and Zulu samples. We will present early results from our evaluation of the different sequencing technologies

April 21, 2020  |  

The use of Online Tools for Antimicrobial Resistance Prediction by Whole Genome Sequencing in MRSA and VRE.

The antimicrobial resistance (AMR) crisis represents a serious threat to public health and has resulted in concentrated efforts to accelerate development of rapid molecular diagnostics for AMR. In combination with publicly-available web-based AMR databases, whole genome sequencing (WGS) offers the capacity for rapid detection of antibiotic resistance genes. Here we studied the concordance between WGS-based resistance prediction and phenotypic susceptibility testing results for methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin resistant Enterococcus (VRE) clinical isolates using publicly-available tools and databases.Clinical isolates prospectively collected at the University of Pittsburgh Medical Center between December 2016 and December 2017 underwent WGS. Antibiotic resistance gene content was assessed from assembled genomes by BLASTn search of online databases. Concordance between WGS-predicted resistance profile and phenotypic susceptibility as well as sensitivity, specificity, positive and negative predictive values (NPV, PPV) were calculated for each antibiotic/organism combination, using the phenotypic results as the gold standard.Phenotypic susceptibility testing and WGS results were available for 1242 isolate/antibiotic combinations. Overall concordance was 99.3% with a sensitivity, specificity, PPV, NPV of 98.7% (95% CI, 97.2-99.5%), 99.6% (95 % CI, 98.8-99.9%), 99.3% (95% CI, 98.0-99.8%), 99.2% (95% CI, 98.3-99.7%), respectively. Additional identification of point mutations in housekeeping genes increased the concordance to 99.4% and the sensitivity to 99.3% (95% CI, 98.2-99.8%) and NPV to 99.4% (95% CI, 98.4-99.8%).WGS can be used as a reliable predicator of phenotypic resistance for both MRSA and VRE using readily-available online tools.Copyright © 2019. Published by Elsevier Ltd.

April 21, 2020  |  

Hybrid sequencing-based personal full-length transcriptomic analysis implicates proteostatic stress in metastatic ovarian cancer.

Comprehensive molecular characterization of myriad somatic alterations and aberrant gene expressions at personal level is key to precision cancer therapy, yet limited by current short-read sequencing technology, individualized catalog of complete genomic and transcriptomic features is thus far elusive. Here, we integrated second- and third-generation sequencing platforms to generate a multidimensional dataset on a patient affected by metastatic epithelial ovarian cancer. Whole-genome and hybrid transcriptome dissection captured global genetic and transcriptional variants at previously unparalleled resolution. Particularly, single-molecule mRNA sequencing identified a vast array of unannotated transcripts, novel long noncoding RNAs and gene chimeras, permitting accurate determination of transcription start, splice, polyadenylation and fusion sites. Phylogenetic and enrichment inference of isoform-level measurements implicated early functional divergence and cytosolic proteostatic stress in shaping ovarian tumorigenesis. A complementary imaging-based high-throughput drug screen was performed and subsequently validated, which consistently pinpointed proteasome inhibitors as an effective therapeutic regime by inducing protein aggregates in ovarian cancer cells. Therefore, our study suggests that clinical application of the emerging long-read full-length analysis for improving molecular diagnostics is feasible and informative. An in-depth understanding of the tumor transcriptome complexity allowed by leveraging the hybrid sequencing approach lays the basis to reveal novel and valid therapeutic vulnerabilities in advanced ovarian malignancies.

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