Russell Higuchi

High‐resolution, high‐throughput HLA genotyping by next‐generation sequencing

The human leukocyte antigen (HLA) class I and class II loci are the most polymorphic genes in the human genome. Hematopoietic stem cell transplantation requires allele-level HLA typing at multiple loci to select the best matched unrelated donors for recipient patients. In current methods for HLA typing, both alleles of a heterozygote are amplified and typed or sequenced simultaneously, often making it difficult to unambiguously determine the sequence of the two alleles. Next-generation sequencing methods clonally propagate in parallel millions of single DNA molecules, which are then also sequenced in parallel. Recently, the read lengths obtainable by one such next-generation sequencing method (454 Life Sciences, Inc.) have increased to >250 nucleotides. These clonal read lengths make possible setting the phase of the linked polymorphisms within an exon and thus the unambiguous determination of the sequence of each HLA allele. Here we demonstrate this capacity as well as show that the throughput of the system is sufficiently high to enable a complete, 7-locus HLA class I and II typing for 24 or 48 individual DNAs in a single GS FLX sequencing run. Highly multiplexed amplicon sequencing is facilitated by the use of sample-specific internal sequence tags (multiplex identification tags or MIDs) in the primers that allow pooling of samples yet maintain the ability to assign sequences to specific individuals. We have incorporated an HLA typing software application developed by Conexio Genomics (Freemantle, Australia) that assigns HLA genotypes for these 7 loci (HLA-A, -B, -C, DRB1, DQA1, DQB1, DPB1), as well as for DRB3, DRB4, and DRB5 from 454 sequence data. The potential of this HLA sequencing system to analyze chimeric mixtures is demonstrated here by the detection of a rare HLA-B allele in a mixture of two homozygous cell lines (1/100), as well as by the detection of the rare nontransmitted maternal allele present in the blood of a severe combined immunodeficiency disease syndrome (SCIDS) patient.

Transcriptional Analysis of Multiple Sclerosis Brain Lesions Reveals a Complex Pattern of Cytokine Expression

Multiple sclerosis (MS) is a common and severe neurological disorder associated with an autoimmune response directed against myelin components within the CNS. Lymphocyte activation, extravasation, and recruitment, as well as effector function, involves the turning on and off of a number of genes, thus triggering specific transcriptional pathways. The characterization of the transcriptome in MS lesions should provide a better understanding of the mechanisms that generate and sustain the pathogenic immune response in this disease. Here we performed transcriptional profiling of 56 relevant genes in brain specimens from eight MS patients and eight normal controls by kinetic RT-PCR. Results showed a high transcriptional activity for the gene coding for myelin basic protein (MBP); however, it was not differentially expressed in MS samples, suggesting that remyelination is an active process also in the noninflammatory brain. CD4 and HLA-DRα transcripts were dramatically increased in MS as compared with controls. This reveals a robust MHC class II up-regulation and suggests that Ag is being presented locally to activated T cells. Although analysis of cytokine and cytokine receptor genes expression showed predominantly increased levels of several Th1 molecules (TGF-β, RANTES, and macrophage-inflammatory protein (MIP)-1α) in MS samples, some Th2 genes (IL-3, IL-5, and IL-6/IL-6R) were found to be up-regulated as well. Similarly, both proinflammatory type (CCR1, CCR5) and immunomodulatory type (CCR4, CCR8) chemokine receptors were differentially expressed in the MS brain. Overall, our data suggest a complex regulation of the inflammatory response in human autoimmune demyelination.

Reproducibility of HPV 16 and HPV 18 viral load quantitation using TaqMan real-time PCR assays

A reproducibility study was designed to assess within-assay, between-day, and interlaboratory variability of three real-time PCR assays targeting HPV 16, HPV 18, and the human glyceraldehyde-3-phosphate dehydrogenase (GAPDH) pseudogenes. Fifteen HPV 16 and fifteen HPV 18 cervical swab samples were amplified in triplicate by GAPDH and HPV 16 and by GAPDH and HPV 18 assays, respectively. All samples were amplified undiluted and at a 1:10 dilution on 2 separate days in the same laboratory, and the same samples were amplified in a separate laboratory. HPV 16 and HPV 18 normalized viral load is reported as the number of HPV genomes per 20000 GAPDH copies. The analytic specificity of the HPV 16 and 18 assays was 100 and 97%, respectively. The intraclass correlation coefficients (ICC) were 0.99, 0.97, and 0.98 for HPV 16, HPV 18, and GAPDH, respectively, indicating that the variability due to experimental error was very low. Ten-fold differences in viral load could be readily discriminated across a six order of magnitude dynamic range (ca. 5-5x10(6) copies). Power of discrimination was increased at higher target concentrations (>5000 copies). The correlation of normalized HPV 16 and 18 viral load was high between the two laboratories (Spearman rho (rho)=0.96 and 0.87, respectively). These HPV 16 and HPV 18 quantitative PCR assays with GAPDH normalization are reproducibly quantitative over a broad linear dynamic range allowing for application in epidemiologic studies for measurement of viral load.

Prediction and diagnosis of bladder cancer recurrence based on urinary content of hTERT, SENP1, PPP1CA, and MCM5 transcripts

BackgroundIdentification of urinary biomarkers for detection of bladder cancer recurrence would be beneficial to minimize the frequency of cystoscopy. Our objective was to determine the usability of urine content of mRNA in the detection and prediction of bladder cancer recurrence.MethodsWe analyzed 123 prospectively cross-sectional collected urine samples from 117 patients with bladder cancer (12 incident cancers and 111 control visits). We used biopsies from cystoscopies as diagnostic criteria for recurrence, and followed the patients for a median time of 28.5 months (range 0-44 months). We measured the levels of hTERT, SENP1, PPP1CA, and MCM5 mRNA in urine by q-RT- PCR.ResultsWe found significant differences in urinary content of hTERT (p < 0.001), SENP1 (p < 0.001), MCM5 (p < 0.001), and PPP1CA (p < 0.001) transcripts, when comparing urine samples from patients with and without tumor present in the bladder. We obtained sensitivity and specificity values for hTERT: 63/73, SENP1: 56/78, MCM5: 63/66, and PPP1CA: 69/63, respectively. Including follow-up data resulted in sensitivity and specificity values for hTERT: 62/84, SENP1:53/84, MCM5: 61/73, and PPP1CA: 65/66. Interestingly, at non-tumor visits the urinary content of especially hTERT (p = 0.0001) and MCM5 (p = 0.02) were significantly associated with subsequent tumour recurrence. Combining the markers with cytology improved the detection. The best combination was hTERT and cytology with a sensitivity of 71% and a specificity of 86% after follow-up. Further prospective validation or registration studies needs to be carried out before clinical use.ConclusionsWe could use the urinary content of hTERT, SENP1, PPP1CA, and MCM5 to detect bladder cancer recurrence. All markers showed a higher sensitivity than cytology. The detection rate improved when including cytology results, but also the combination of hTERT and MCM5 increased the detection rate. Furthermore, hTERT and MCM5 levels predicted subsequent tumor recurrences.

Chromosome Translocations in Workers Exposed to Benzene

As benzene has been linked with elevated risk of both acute myeloid leukemia and lymphoma, we explored the effect of benzene exposure on levels of t(8;21), t(15;17), and t(14;18) translocations. Circulating lymphocytes of normal individuals also often contain t(14;18). Quantitative polymerase chain reaction analysis showed that 37 workers with benzene exposure had a decreased level of t(14;18) in their blood with only 16.2% having 10 or more copies of the t(14;18) BCL-2/IgH fusion gene/microg DNA, as opposed to 55% of 20 controls (P = .0063 by Fishers exact test). This decline may be related to the immunotoxicity to specific subtypes of circulating B-lymphocytes, but the data do not support the use of t(14;18) as a biomarker of increased lymphoma risk in benzene-exposed populations. None of 88 individuals (31 controls and 57 exposed) exhibited detectable t(8;21) transcripts, and while t(15;17) transcripts were detected in two individuals, the result is inconclusive as one was exposed and the other was unexposed.

Quantitation of residual WBCs in filtered blood components by high-throughput, real-time kinetic PCR

BACKGROUND: The effort to eliminate transfusion complications associated with WBCs has led to the widespread use of filters able to reduce WBC concentrations to ≤0.1 WBC per μL blood. This has necessitated sensitive QC methods to quantitate residual WBCs in filtered units. One fast, effective method is DNA amplification using real‐time kinetic PCR (kPCR).

SNP Discovery and Genotyping

The identification of genes affecting complex traits (i.e., biological traits affected by several genetic and environmental factors) is a very difficult and challenging task (1, 2, 3). For many complex traits, the observable variation between individuals is quantitative; hence, loci affecting such traits are generally termed quantitative trait loci (QTLs). In contrast with monogenic traits, it is impossible to identify all the genomic regions responsible for complex trait variation without additional information on how these regions segregate (1,4). A key development in complex trait analysis was the establishment of large collections of molecular/genetic markers. With the discovery of a large amount of single nucleotide polymorphisms (SNPs) in human and model organisms, correlating SNP markers with phenotype in a segregating population has become a useful tool in QTL studies (5). In both linkage and association mapping, the development of high-throughput methods to discover and genotype polymorphism markers has enabled whole-genome scanning to detect individual loci possible (2).