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OBJECTIVE The purpose was to test the hypothesis that the HLA-DQαβ heterodimer structure is related to the progression of islet autoimmunity from asymptomatic to symptomatic type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS Next-generation targeted sequencing was used to genotype HLA-DQA1-B1 class II genes in 670 subjects in the Diabetes Prevention Trial–Type 1 (DPT-1). Coding sequences were translated into DQ α- and β-chain amino acid residues and used in hierarchically organized haplotype (HOH) association analysis to identify motifs associated with diabetes onset. RESULTS The opposite diabetes risks were confirmed for HLA DQA1*03:01-B1*03:02 (hazard ratio [HR] 1.36; P = 2.01 ∗ 10−3) and DQA1*03:03-B1*03:01 (HR 0.62; P = 0.037). The HOH analysis uncovered residue −18β in the signal peptide and β57 in the β-chain to form six motifs. DQ*VA was associated with faster (HR 1.49; P = 6.36 ∗ 10−4) and DQ*AD with slower (HR 0.64; P = 0.020) progression to diabetes onset. VA/VA, representing DQA1*03:01-B1*03:02 (DQ8/8), had a greater HR of 1.98 (P = 2.80 ∗ 10−3). The DQ*VA motif was associated with both islet cell antibodies (P = 0.023) and insulin autoantibodies (IAAs) (P = 3.34 ∗ 10−3), while the DQ*AD motif was associated with a decreased IAA frequency (P = 0.015). Subjects with DQ*VA and DQ*AD experienced, respectively, increasing and decreasing trends of HbA1c levels throughout the follow-up. CONCLUSIONS HLA-DQ structural motifs appear to modulate progression from islet autoimmunity to diabetes among at-risk relatives with islet autoantibodies. Residue −18β within the signal peptide may be related to levels of protein synthesis and β57 to stability of the peptide-DQab trimolecular complex.

Dogs have served as one of the most reliable preclinical models for a variety of diseases and treatments, including stem/progenitor cell transplantation. At the genetic epicenter of dog transplantation models, polymorphic major histocompatibility complex (MHC) genes are most impactful on transplantation success. Among the canine class I and class II genes, DLA-88 has been best studied in transplantation matching and outcomes, with 129 DLA-88 alleles identified. In this study we developed and tested a next generation (NGS) sequencing protocol for rapid identification of DLA-88 genotypes in dogs and compared the workflow and data generated with an established DLA-88 Sanger sequencing protocol that has been in common prior use for clinical studies. By testing the NGS protocol on a random population of 382 dogs, it was possible to demonstrate superior efficacy based on laboratory execution and overall cost. In addition, NGS proved far more effective at discovering new alleles and detecting multiple alleles associated with gene duplication. A total of 51 new DLA-88 alleles are reported here. This rate of new allele discovery indicates that a large pool of yet un-discovered DLA-88 alleles exists in the domestic dog population. In addition, more than 46% of dogs carried three or more copies of DLA-88, further emphasizing the need for more sensitive and cost-effective DLA typing methodology for the dog clinical model.

HLA-DQA1 and -DQB1 genes have significant and potentially causal associations with autoimmune type 1 diabetes (T1D). To follow up on the earlier analysis on high-risk HLA-DQ2.5 and DQ8.1, the current analysis uncovers seven residues (αa1, α157, α196, β9, β30, β57, and β70) that are resistant to T1D among subjects with DQ4-, 5-, 6-, and 7-resistant DQ haplotypes. These 7 residues form 13 common motifs: 6 motifs are significantly resistant, 6 motifs have modest or no associations (P values >0.05), and 1 motif has 7 copies observed among control subjects only. The motifs “DAAFYDG,” “DAAYHDG,” and “DAAYYDR” have significant resistance to T1D (odds ratios [ORs] 0.03, 0.25, and 0.18; P = 6.11 × 10−24, 3.54 × 10−15, and 1.03 × 10−21, respectively). Remarkably, a change of a single residue from the motif “DAAYHDG” to “DAAYHSG” (D to S at β57) alters the resistance potential, from resistant motif (OR 0.15; P = 3.54 × 10−15) to a neutral motif (P = 0.183), the change of which was significant (Fisher P value = 0.0065). The extended set of linked residues associated with T1D resistance and unique to each cluster of HLA-DQ haplotypes represents facets of all known features and functions of these molecules: antigenic peptide binding, peptide–MHC class II complex stability, β167-169 RGD loop, T-cell receptor binding, formation of homodimer of α-β heterodimers, and cholesterol binding in the cell membrane rafts. Identification of these residues is a novel understanding of resistant DQ associations with T1D. Our analyses endow potential molecular approaches to identify immunological mechanisms that control disease susceptibility or resistance to provide novel targets for immunotherapeutic strategies.

HLA-DQA1 and -DQB1 are strongly associated with type 1 diabetes (T1D), and DQ8.1 and DQ2.5 are major risk haplotypes. Next-generation targeted sequencing of HLA-DQA1 and -DQB1 in Swedish newly diagnosed 1- to 18 year-old patients (n = 962) and control subjects (n = 636) was used to construct abbreviated DQ haplotypes, converted into amino acid (AA) residues, and assessed for their associations with T1D. A hierarchically organized haplotype (HOH) association analysis allowed 45 unique DQ haplotypes to be categorized into seven clusters. The DQ8/9 cluster included two DQ8.1 risk and the DQ9 resistant haplotypes, and the DQ2 cluster included the DQ2.5 risk and DQ2.2 resistant haplotypes. Within each cluster, HOH found residues α44Q (odds ratio [OR] 3.29, P = 2.38 * 10−85) and β57A (OR 3.44, P = 3.80 * 10−84) to be associated with T1D in the DQ8/9 cluster representing all ten residues (α22, α23, α44, α49, α51, α53, α54, α73, α184, β57) due to complete linkage disequilibrium (LD) of α44 with eight such residues. Within the DQ2 cluster and due to LD, HOH analysis found α44C and β135D to share the risk for T1D (OR 2.10, P = 1.96 * 10−20). The motif “QAD” of α44, β57, and β135 captured the T1D risk association of DQ8.1 (OR 3.44, P = 3.80 * 10−84), and the corresponding motif “CAD” captured the risk association of DQ2.5 (OR 2.10, P = 1.96 * 10−20). Two risk associations were related to GAD65 autoantibody (GADA) and IA-2 autoantibody (IA-2A) but in opposite directions. CAD was positively associated with GADA (OR 1.56, P = 6.35 * 10−8) but negatively with IA-2A (OR 0.59, P = 6.55 * 10−11). QAD was negatively associated with GADA (OR 0.88; P = 3.70 * 10−3) but positively with IA-2A (OR 1.64; P = 2.40 * 10−14), despite a single difference at α44. The residues are found in and around anchor pockets 1 and 9, as potential T-cell receptor contacts, in the areas for CD4 binding and putative homodimer formation. The identification of three HLA-DQ AAs (α44, β57, β135) conferring T1D risk should sharpen functional and translational studies.

SARS-CoV-2 is spreading worldwide with continuously evolving variants, some of which occur in the Spike protein and appear to increase the viral transmissibility. However, variants that cause severe COVID-19 or lead to other breakthroughs have not been well characterized. To discover such viral variants, we assembled a cohort of 683 COVID-19 patients; 388 inpatients (“cases”) and 295 outpatients (“controls”) from April to August 2020 using electronically captured COVID test request forms and sequenced their viral genomes. To improve the analytic power, we accessed 7,137 viral sequences in Washington State to filter out viral single nucleotide variants (SNVs) that did not have significant expansions over the collection period. Applying this filter led to the identification of 53 SNVs that were statistically significant, of which 13 SNVs each had 3 or more variant copies in the discovery cohort. Correlating these selected SNVs with case/control status, eight SNVs were found to significantly associate with inpatient status (q-values−11) that appeared in April 2020, peaked in June, and persisted into January 2021. This association was replicated (OR=5.46, p-value=4.71*10−12) in an independent cohort of 964 COVID-19 patients (June 1, 2020 to March 31, 2021). The haplotype included a synonymous change N73N in endoRNase, and three non-synonymous changes coding residues R203K, R203S and G204R in the nucleocapsid protein. This discovery points to the potential functional role of the nucleocapsid protein in triggering “cytokine storms” and severe COVID-19 that led to hospitalization. The study further emphasizes a need for tracking and analyzing viral sequences in correlations with clinical status.

SARS-CoV-2 is spreading worldwide with continuously evolving variants, some of which occur in the Spike protein and appear to increase the viral transmissibility. However, variants that cause severe COVID-19 or lead to other breakthroughs have not been well characterized. To discover such viral variants, we assembled a cohort of 683 COVID-19 patients; 388 inpatients (“cases”) and 295 outpatients (“controls”) from April to August 2020 using electronically captured COVID test request forms and sequenced their viral genomes. To improve the analytic power, we accessed 7,137 viral sequences in Washington State to filter out viral single nucleotide variants (SNVs) that did not have significant expansions over the collection period. Applying this filter led to the identification of 53 SNVs that were statistically significant, of which 13 SNVs each had 3 or more variant copies in the discovery cohort. Correlating these selected SNVs with case/control status, eight SNVs were found to significantly associate with inpatient status (q-values

Many clinical laboratories supporting solid organ transplant programs use multiple HLA genotyping technologies, depending on individual laboratory needs. Sequence‐specific primers and quantitative polymerase chain reaction (qPCR) serve the rapid turnaround necessary for deceased donor workup, while sequence‐specific oligonucleotide probe (SSOP) technology is widely employed for higher volumes. When clinical need mandates high‐resolution data, Sanger sequencing‐based typing (SBT) has been the “gold standard.” However, all those methods commonly yield ambiguous typing results that utilize valuable laboratory resources when resolution is required. In solid organ transplantation, high‐resolution typing may provide critical information for highly sensitized patients with donor‐specific anti‐HLA antibodies (DSA), particularly when DSA involve HLA alleles not discriminated by SSOP typing. Arguments against routine use of SBT include assay complexity, long turnaround times (TAT), and increased costs. Here, we compare a next generation sequencing (NGS) technology with SSOP for accuracy, effort, turnaround time, and level of resolution for genotyping of 11 HLA loci among 289 specimens from five clinical laboratories. Results were concordant except for SSOP misassignments in eight specimens and 21 novel sequences uniquely identified by NGS. With few exceptions, SSOP generated ambiguous results while NGS provided unambiguous three‐field allele assignments. For complete HLA genotyping of up to 24 samples by either SSOP or NGS, bench work was completed on day 1 and typing results were available on day 2. This study provides compelling evidence that, although not viable for STAT typing of deceased donors, a single‐pass NGS HLA typing method has direct application for solid organ transplantation.

Next-generation targeted sequencing of HLA-DRB1 and HLA-DRB3, -DRB4, and -DRB5 (abbreviated as DRB345) provides high resolution of functional variant positions to investigate their associations with type 1 diabetes risk and with autoantibodies against insulin (IAA), GAD65 (GADA), IA-2 (IA-2A), and ZnT8 (ZnT8A). To overcome exceptional DR sequence complexity as a result of high polymorphisms and extended linkage disequilibrium among the DR loci, we applied a novel recursive organizer (ROR) to discover disease-associated amino acid residues. ROR distills disease-associated DR sequences and identifies 11 residues of DRB1, sequences of which retain all significant associations observed by DR genes. Furthermore, all 11 residues locate under/adjoining the peptide-binding groove of DRB1, suggesting a plausible functional mechanism through peptide binding. The 15 residues of DRB345, located respectively in the β49–55 homodimerization patch and on the face of the molecule shown to interact with and bind to the accessory molecule CD4, retain their significant disease associations. Further ROR analysis of DR associations with autoantibodies finds that DRB1 residues significantly associated with ZnT8A and DRB345 residues with GADA. The strongest association is between four residues (β14, β25, β71, and β73) and IA-2A, in which the sequence ERKA confers a risk association (odds ratio 2.15, P = 10−18), and another sequence, ERKG, confers a protective association (odds ratio 0.59, P = 10−11), despite a difference of only one amino acid. Because motifs of identified residues capture potentially causal DR associations with type 1 diabetes, this list of residuals is expected to include corresponding causal residues in this study population.

Background: SARS-CoV-2 is continuously evolving with the emergence of variants of interest (VOI) or with variants of concern (VOC). While Variants of High Consequence (VOHC) are well defined, no such variants have been formally documented. Here we propose an integrated strategy and application towards discovering VOHC. Methods: We utilized 7,137 viral sequences collected from COVID-19 cases in Washington State from January 19, 2020 to January 31, 2021, to identify genome-wide viral single nucleotide variants (SNVs). Utilizing a non-parametric regression model, we selected a subset of SNVs that had significant and substantial expansions over the collection period. Further, using unsupervised learning, we identified multiple SNVs forming haplotypes. To evaluate their clinical relevance, we assembled a discovery cohort of COVID-19 cases (388 inpatients and 295 outpatients) to identify SNVs and haplotypes associated with hospitalization status, a proxy for disease severity. A logistic regression model was used to assess associations of SNVs with hospitalization status in the discovery cohort. These results were validated on an independent cohort of 964 genome sequences derived from COVID-19 cases in Washington State from June 1, 2020 to March 31, 2021. Finding: The analysis of the 7,137 sequences led to identification of 107 SNVs that were statistically significant (false positive error rate q-value 0.10). Forty-one SNVs were considered urgent, because their SNV proportions persisted or expanded above 10% in January 2021, the last month of the current investigation period. Correlating with clinical data, eight SNVs were found to significantly associate with inpatient status (p-values

Background: HLA-DR4, a common antigen of HLA-DRB1, has multiple subtypes that are strongly associated with risk of type 1 diabetes (T1D); however, some are risk neutral or resistant. The pathobiological mechanism of HLA-DR4 subtypes remains to be elucidated. Methods: We used a population-based case-control study of T1D (962 patients and 636 controls) to decipher genetic associations of HLA-DR4 subtypes and specific residues with susceptibility to T1D. Using a birth cohort of 7865 children with periodically measured islet autoantibodies (GADA, IAA or IA-2A), we proposed to validate discovered genetic associations with a totally different study design and time-to-seroconversions prior to clinical onset of T1D. A novel analytic strategy hierarchically organized the HLA-DRB1 alleles by sequence similarity and identified critical amino acid residues by minimizing local genomic architecture and higher-order interactions. Findings: Three amino acid residues of HLA-DRB1 (β71, β74, β86) were found to be predictive of T1D risk in the population-based study. The “KAG” motif, corresponding to HLA-DRB1×04:01, was most strongly associated with T1D risk ([O]dds [R]atio=3.64, p = 3.19 × 10−64). Three less frequent motifs (“EAV”, OR = 2.55, p = 0.025; “RAG”, OR = 1.93, p = 0.043; and “RAV”, OR = 1.56, p = 0.003) were associated with T1D risk, while two motifs (“REG” and “REV”) were equally protective (OR = 0.11, p = 4.23 × 10−4). In an independent birth cohort of HLA-DR3 and HLA-DR4 subjects, those having the “KAG” motif had increased risk for time-to-seroconversion (Hazard Ratio = 1.74, p = 6.51 × 10−14) after adjusting potential confounders. Interpretations: DNA sequence variation in HLA-DRB1 at positions β71, β74, and β86 are non-conservative (β74 A→E, β71 E vs K vs R and β86 G vs V). They result in substantial differences in peptide antigen anchor pocket preferences at p1, p4 and potentially neighboring regions such as pocket p7. Differential peptide antigen binding is likely to be affected. These sequence substitutions may account for most of the HLA-DR4 contribution to T1D risk as illustrated in two HLA-peptide model complexes of the T1D autoantigens preproinsulin and GAD65. Funding: National Institute of Diabetes and Digestive and Kidney Diseases and the Swedish Child Diabetes Foundation and the Swedish Research Council.

HLA-DQA1 and -DQB1 genes have significant and potentially causal associations with autoimmune type 1 diabetes (T1D). To follow on the earlier analysis on high-risk HLA-DQ2.5 and DQ8.1, the current analysis uncovers seven residues (αa1, α157, α196, β9, β30, β57, β70) that are resistant to T1D among subjects with DQ4, 5, 6 and 7 resistant DQ haplotypes. These seven residues form 13 common motifs; six motifs are significantly resistant, six motifs have modest or no associations (p-values>0.05), and one motif has 7 copies observed among controls only. The motif “DAAFYDG”, “DAAYHDG” and “DAAYYDR” have significant resistance to T1D (OR = 0.03, 0.25 and 0.18, p-value = 6.11*10-24, 3.54*10-15 and 1.03*10-21, respectively). Remarkably, a change of a single residue from the motif “DAAYHDG” to “DAAYHSG” (D to S at β57) alters the resistance potential, from resistant motif (OR = 0.15, p-value = 3.54*10-15) to a neutral motif (p-value = 0.183), the change of which was significant (Fisher’s p-value = 0.0065). The extended set of linked residues associated with T1D resistance and unique to each cluster of HLA-DQ haplotypes represents facets of all known features and functions of these molecules: antigenic peptide binding, pMHCII complex stability, b167-169 RGD loop, TCR binding, formation of homodimer of alpha-beta heterodimers, and cholesterol binding in the cell membrane rafts. Identifications of these residues is a novel understanding of resistant DQ associations with T1D. Our analyses endow potential molecular approaches to identify immunological mechanisms that control disease susceptibility or resistance to provide novel targets for immunotherapeutic strategies.

HLA-DQA1 and -DQB1 are strongly associated with type 1 diabetes (T1D), and DQ8.1 and DQ2.5 are major risk haplotypes. Next generation targeted sequencing of HLA-DQA1 and -DQB1 in Swedish newly diagnosed 1-18 year-old patients (n=962) and controls (n=636) was used to construct abbreviated DQ haplotypes, converted into amino acid (AA) residues, and assessed for their associations with T1D. A hierarchically-organized haplotype (HOH) association analysis, allowed 45 unique DQ haplotypes to be categorized into seven clusters. The DQ8/9 cluster included two DQ8.1 risk and the DQ9 resistant haplotypes, and the DQ2 cluster, included the DQ2.5 risk and DQ2.2 resistant haplotypes. Within each cluster, HOH found residues α44Q (OR 3.29, p=2.38*10-85 ) and β57A (OR 3.44, p=3.80*10-84) to be associated with T1D in the DQ8/9 cluster representing all ten residues (α22, α23, α44, α49, α51, α53, α54, α73, α184, β57) due to complete linkage-disequilibrium (LD) of α44 with eight such residues. Within the DQ2 cluster and due to LD, HOH analysis found α44C and β135D to share the risk for T1D (OR 2.10, p=1.96*10-20). The motif “QAD” of α44, β57, and β135 captured the T1D risk association of DQ8.1 (OR 3.44, p=3.80*10-84), the corresponding motif “CAD” captured the risk association of DQ2.5 (OR 2.10, p=1.96*10-20). Two risk associations were related to GADA and IA-2A, but in opposite directions. “CAD” was positively associated with GADA (OR 1.56; p=6.35*10-8) but negatively with IA-2A (OR 0.59, p= 6.55*10-11). “QAD” was negatively associated with GADA (OR 0.88; p= 3.70*10-3) but positively with IA-2A (OR 1.64; p= 2.40*10-14), despite a single difference at α44. The residues are found in and around anchor pockets 1 and 9, as potential TCR contacts, in the areas for CD4 binding and putative homodimer formation. The identification of three HLA-DQ AA (α44, β57, β135) conferring T1D risk should sharpen functional and translational studies.

A line of investigations indicate that genes in the human leukocyte antigen (HLA) complex are involved in a successful acceptance of the semiallogeneic fetus during pregnancy. In this study, associations between specific HLA class Ia (HLA-A and -B) and class II (HLA-DRB1, -DQA1, -DQB1, -DPA1 and -DPB1) alleles and the risk of developing severe preeclampsia/eclampsia were investigated in a detailed and large-scale study. In total, 259 women diagnosed with severe preeclampsia or eclampsia and 260 matched control women with no preeclampsia, together with their neonates, were included in the study. HLA genotyping for mothers and neonates was performed using next-generation sequencing. The HLA-DPB1*04:01:01G allele was significantly more frequent (Pc=0.044) among women diagnosed with severe preeclampsia/eclampsia compared with controls, and the DQA1*01:02:01G allele frequency was significantly lower (Pc=0.042) among newborns born by women with severe preeclampsia/eclampsia compared with controls. In mothers with severe preeclampsia/eclampsia, homozygosity was significantly more common compared with controls at the HLA-DPB1 locus (Pc=0.0028). Although the current large study shows some positive results, more studies, also with a functional focus, are needed to further clarify a possible role of the classical HLA genes in preeclampsia.

The possible contribution of HLA-DRB3, -DRB4, and -DRB5 alleles to type 1 diabetes risk and to insulin autoantibody (IAA), GAD65 (GAD autoantibody [GADA]), IA-2 antigen (IA-2A), or ZnT8 against either of the three amino acid variants R, W, or Q at position 325 (ZnT8RA, ZnT8WA, and ZnT8QA, respectively) at clinical diagnosis is unclear. Next-generation sequencing (NGS) was used to determine all DRB alleles in consecutively diagnosed patients ages 1–18 years with islet autoantibody–positive type 1 diabetes (n = 970) and control subjects (n = 448). DRB3, DRB4, or DRB5 alleles were tested for an association with the risk of DRB1 for autoantibodies, type 1 diabetes, or both. The association between type 1 diabetes and DRB1*03:01:01 was affected by DRB3*01:01:02 and DRB3*02:02:01. These DRB3 alleles were associated positively with GADA but negatively with ZnT8WA, IA-2A, and IAA. The negative association between type 1 diabetes and DRB1*13:01:01 was affected by DRB3*01:01:02 to increase the risk and by DRB3*02:02:01 to maintain a negative association. DRB4*01:03:01 was strongly associated with type 1 diabetes (P = 10−36), yet its association was extensively affected by DRB1 alleles from protective (DRB1*04:03:01) to high (DRB1*04:01:01) risk, but its association with DRB1*04:05:01 decreased the risk. HLA-DRB3, -DRB4, and -DRB5 affect type 1 diabetes risk and islet autoantibodies. HLA typing with NGS should prove useful to select participants for prevention or intervention trials.

Clinical immunogenetics laboratories performing routine sequencing of human leukocyte antigen (HLA) genes in support of hematopoietic cell transplantation are motivated to upgrade to next-generation sequencing (NGS) technology by its potential for cost savings as well as testing accuracy and flexibility. While NGS machines are available and simple to operate, there are few systems available that provide comprehensive sample preparation and data analysis workflows to complete the process. We report on the development and testing of the Integrated Genotyping System (IGS), which has been designed to specifically address the challenges associated with the adoption of NGS in clinical laboratories. To validate the system for a variety of sample DNA sources, we have tested 336 DNA specimens from whole blood, dried blood spots, buccal swabs, and lymphoblastoid cell lines. HLA class I and class II genotypes were derived from amplicon sequencing of HLA-A, -B, -C for exons 1–7 and HLA-DPA1, -DPB1, -DQA1, -DQB1, -DRB1, -DRB3, -DRB4, -DRB5 for exons 1–4. Additionally, to demonstrate the extensibility of the IGS to other genetic loci, KIR haplotyping of 93 samples was carried out in parallel with HLA typing using a workflow based on the HLA system. These results are discussed with respect to their applications in the clinical setting and consequent potential for advancing precision medicine.

Introduction Accuracy and precision are critically important in the assessment of minimal residual disease (MRD) and chimerism following hematopoietic cell transplantation. Reliable and sensitive detection of changes in engraftment status can impact patient care by early detection of potential failure of engraftment or relapse. We evaluated a commercially available NGS technology for engraftment monitoring for sensitivity, accuracy and reproducibility. Objective Introduction of next generation sequencing technology for engraftment monitoring. Methods Samples analyzed by NGS at Baylor Transplant Immunology Laboratory included archived clinical specimens with historic results by STR, n=19, or qPCR, n=15, test results; 72 artificial mixtures of volunteer donors, and 5 ASHI external proficiency specimens. NGS analysis assessed 182 SNPs validated in the 1000 Genomes HapMap project and distributed across all 23 chromosomes, including the x chromosome. The rapid workflow allows a TAT of 2 days for up to 24 samples, with a less than 6 hour NGS library preparation protocol, followed by a 6 hour sequencing run time and 30 minute analysis. The low sample requirement, 1 ng DNA per PCR, facilitates chimerism assessment in multiple cell subsets including low frequency populations such as CD34-positive cells. Results NGS showed close concordance with historic results from STR and qPCR (figure 1), providing validation of NGS technology. Figure 2 compares NGS results versus the reference values of artificial mixtures and demonstrates NGS accuracy, while the low tech to tech variation data reveals assay precision. Limit of detection experiments showed reliable 0.1% sensitivity, as illustrated in Figure 3, with NGS analysis of 4 mixtures at 0.1%.. In addition, NGS reported results for the external proficiency samples correlated closely with the mean % donor reported throughout the full range of donor/recipient proportions including concordance with a sample of 100% donor. Conclusions Application of NGS technology to chimerism analysis in HCT provides accurate and precise test results. With the reliable 0.1% sensitivity and low input DNA that allows testing of multiple critical cell subsets, NGS is particularly relevant to early detection of MRD, graft failure, and relapse.

Ensemble-decision aliquot ranking (eDAR) is a sensitive and high-throughput method to analyze circulating tumor cells (CTCs) from peripheral blood. Here, we report the next generation of eDAR, where we designed and optimized a new hydrodynamic switching scheme for the active sorting step in eDAR, which provided fast cell sorting with an improved reproducibility and stability. The microfluidic chip was also simplified by incorporating a functional area for subsequent purification using microslits fabricated by standard lithography method. Using the reported second generation of eDAR, we were able to analyze 1 mL of whole-blood samples in 12.5 min, with a 95% recovery and a zero false positive rate (n = 15).

AIM: It is of interest to predict possible lifetime risk of type 1 diabetes (T1D) in young children for recruiting high-risk subjects into longitudinal studies of effective prevention strategies.METHODS: Utilizing a case-control study in Sweden, we applied a recently developed next generation targeted sequencing technology to genotype class II genes and applied an object-oriented regression to build and validate a prediction model for T1D.RESULTS: In the training set, estimated risk scores were significantly different between patients and controls (P = 8.12 × 10(-92) ), and the area under the curve (AUC) from the receiver operating characteristic (ROC) analysis was 0.917. Using the validation data set, we validated the result with AUC of 0.886. Combining both training and validation data resulted in a predictive model with AUC of 0.903. Further, we performed a "biological validation" by correlating risk scores with 6 islet autoantibodies, and found that the risk score was significantly correlated with IA-2A (Z-score = 3.628, P < 0.001). When applying this prediction model to the Swedish population, where the lifetime T1D risk ranges from 0.5% to 2%, we anticipate identifying approximately 20 000 high-risk subjects after testing all newborns, and this calculation would identify approximately 80% of all patients expected to develop T1D in their lifetime.CONCLUSION: Through both empirical and biological validation, we have established a prediction model for estimating lifetime T1D risk, using class II HLA. This prediction model should prove useful for future investigations to identify high-risk subjects for prevention research in high-risk populations. (Less)

This paper reviews publications that have fortified our understanding of the electrowetting-on-dielectric (EWOD) actuation mechanism. Over the last decade, growing interest in EWOD has led to a wide range of scientific and technological investigations motivated by its applicability in microfluidics, especially for droplet-based optical and lab-on-a-chip systems. At this point in time, we believe that it is helpful to summarize the observations, insights, and modeling techniques that have led to the current picture showing how forces act on liquid droplets and how droplets respond in EWOD microfluidic devices. We discuss the basic physics of EWOD and explain the mechanical response of a droplet using free-body diagrams. It is our hope that this review will inspire new research approaches and help design useful devices. © 2012 Copyright Taylor and Francis Group, LLC.

Aim The DR2 supertype currently comprises 204 DRB1∗15 and 65 DRB1∗16 alleles. With few exceptions, DR2 alleles associate with one of 46 DRB5 alleles. DRB5-DRB1-DQA1-DQB1 haplotypes may differ among diverse world populations. We used NGS for HLA genotyping of commercial human population panels composed primarily of unrelated individuals. We report here on the 170 DR2 alleles and haplotypes identified among 541 individuals in 6 sample panels. Methods The sample panels were from the Coriell repository: hapmappt02, hapmappt04, hapmappt05, hapmappt06, MGP00010 and MGP00019. Hapmappt06 represents CEPH family pairs and trios. NGS genotyping of HLA-A, B, C, DRB5, DRB1, DQA1, DQB1, DPA1, DPB1 employed an amplicon based technology assessing all exons with intervening intron data to exclude known null alleles. DRB5-DRB1-DQA1-DQB1 haplotypes were inferred based on common associations in publically available data sets: bioinformatics.bethematchclinical.org and the IMGT HLA database. Results Three DRB1∗15 alleles, two DRB1∗16 and three DRB5 alleles were identified on 12 different haplotypes, see Table. DRB1∗15:01:01 was found in 6 associations. Most frequent was DRB5∗0101:01-DRB1∗15:01:01-DQA1∗01:02:01-DQB1∗06:02:01, found in all panels except Gambian. DRB1∗15:02:01, almost exclusive to Asians, was found in 2 linkages, with DRB5∗01:02-DRB1∗15:02:01-DQA1∗01:03:01-DQB1∗06:01:01 most frequent. DRB1∗15:03:01, on DRB5∗01:01:01-DRB1∗15:03:01-DQA1∗01:02:01-DQB1∗06:02:01, was found only in Nigerian. DRB1∗16:01:01, only in Caucasian, associated with DRB5∗02:02-DQA1∗01:02:02-DQB1∗05:02:01. DRB1∗16:02:01, seen in Asian and Gambian, was found most frequently with DRB5∗02:02-DQA1∗01:02:02-DQB1∗05:02:01, but also with DRB5∗01:01:01-DQA1∗01:02:02-DQB1∗05:02:01. Conclusions Seven DR2 haplotypes appear to be the results of historic recombination events. DR2 alleles and haplotypes are diverse and differ among human populations. Download : Download high-res image (718KB) Download : Download full-size image

We report monolithic fabrication of parallel-plate electrowetting-on-dielectric (EWOD) chips for digital micro-fluidics of picoliter droplets. Instead of assembling a second substrate to form a top plate-the common practice with all previous parallel-plate EWOD chips-the top plate is surface micromachined as a transparent thin-film membrane that forms a monolithic cavity having a gap height on the order of micrometers with excellent accuracy and uniformity. The membrane is embedded with EWOD driving electrodes and confines droplets against the device substrate to perform digital microfluidic operations. Two main attributes of the monolithic architecture that distinguish it from tradition methods are: (i) it enables excellent control of droplet dimensions down to the micrometer scale, and (ii) it does not require the typical alignment and assembly steps. Basic device functions such as creation and splitting are verified by EWOD actuation of ~100 picoliter droplets surrounded by air or oil inside a 10 μm-high cavity. Additionally, flow focusing of droplets containing 5.3 μm beads demonstrates one example of the utilities afforded by monolithic fabrication.

Localized heating of droplets on an electrowetting-on-dielectric (EWOD) chip has been implemented and shown to accelerate trypsin digestion reaction rates, sample drying, and matrix crystallization for matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS). Achieving this involved extending the functionality of previous EWOD droplet-based techniques by developing a multifunctional electrode with closed-loop temperature control, while minimizing overall system complexity and addressing challenges associated with rapid evaporation. For the EWOD chip design, we discuss the performance of multifunctional surface electrodes for actuation, localized Joule heating, and thermistic temperature sensing. Furthermore, a hydrophilic pattern is formed in the multifunctional electrode to control the location of an evaporating droplet on the electrode. To demonstrate the capabilities and limitations of this technique, we performed three experiments and measured the results using MALDI-MS: (i) insulin disulfide reductions in dithiothreitol (DTT) over a range of heater temperatures (22-70 °C) to show how reaction rates can be affected by thermal control, (ii) insulin disulfide reductions at 130 °C in dimethyl sulfoxide (DMSO) to demonstrate a reaction in a high boiling point solvent, and (iii) tryptic digestions of cytochrome c at 22 and 40 °C to show that heated droplets can yield reasonably higher peptide sequence coverage than unheated droplets. Although they do not decouple the effects of changing temperatures and concentrations, these experiments verified that thermal cycling by EWOD electrodes accelerates reaction rates in liquid droplets in air.

Aim Family studies are the gold standard for studying HLA haplotype segregation. This information is critical when studying haplotype associations among populations where few members of the population have been typed, rendering bioinformatics algorithms less reliable. Here, we characterize HLA haplotypes in 5 Jamaican families identified through the Caribbean Bone Marrow Registry. Methods Twenty Jamaican individuals of 5 families were tested by NGS HLA genotypes at loci A, B, C, DRB345, DRB1, DQA1, DQB1, DPA1 & DPB1. We initially attempted full gene sequencing but amplification failed repeatedly due to suboptimal DNA quality from buccal swabs. Typing was performed using Scisco Genomics kit on the MiSeq. Identified haplotypes were compared to haplotype frequency ranking among the 5 major US populations (Caucasians (CAU), African Americans (AFA), Hispanics (HIS), Asian Pacific Islanders (API), and Native Americans (NAM)) using the NMDP Haplostats. Haplostats provides data on 6-locus 2-field resolution, which could give a higher estimate than the 9-locus 3-field haplotypes described here. Results Typing was successful in all individuals and all loci except for failed DPB1 typing on 2 subjects due to low DNA quantity. Analysis of 20 members identified 17 unique haplotypes. The most common haplotype among CAU, HIS, and NAM and 2nd most common in AFA (Haplotype A in Table 1) was observed in 3 families. Another haplotype in 2 families (B) was uncommon among CAU, HIS & AFA (ranked 20466, 23219 & 8463, respectively) and not reported in other populations. Overall observed haplotypes were more common in AFA than other population and 2 haplotypes (C & D) were seen only in AFA. One haplotype (E) was seen only in API (ranked 5660). One haplotype (F) was not reported for any population. Conclusions Although the number of tested families is small, this data suggest that the Jamaican population is unique and diverse, and supports the proposition of establishing a local/regional BMT registry to maximize the chances of identifying matched donors.

The mystery began when HLA typing, of two apparently unrelated individuals at two different institutions, identified the presence of a DRB5∗01 gene without any evidence of an expected linked DRB1∗15, DRB1∗16, or, in rare cases, DRB1∗01 allele. Historic data from Sanger sequence-based typing included DRB1∗14, DRB3∗02:02, DRB5∗01:01, DQB1∗05:03, 06:02 for Individual 1 and DRB1∗04:01; DRB4∗01; DRB5∗01:01; DQB1∗03:01, 06:02 for Individual 2. Since those analyses only assessed exon 2, the apparent absence of a DRB1 allele associated with the DRB5 gene raised the possibility of an entire linked DRB1 gene having gone missing. Both specimens were recently re-examined using next generation sequencing technology. HLA-A, B, C genes were assessed for exons 1–7; DRB1, DRB3/B4/B5, DQA1, DQB1, and DPB1 were assessed for exons 1–4; and DPA1 for exons 2–4. In Individual 1, NGS identified DRB1∗14:54:01 and a DRB1∗15 exon 1 sequence, but without any evidence of DRB1∗15 sequences for exons 2 and 3. Since the exon 4 sequences of DRB1∗14:54:01 and DRB1∗15 are identical, it could not be determined whether the DRB1∗15 exon 4 sequence was present. Individual 2, typed as DRB1∗04:01:01 and, again, a DRB1∗15 exon 1. In the latter case, it was clear that no exon 2, 3, or 4 sequences were present for the DRB1∗15 gene, since exon 4 sequences differ between DRB1∗04:01:01 and DRB1∗15. The table shows the full NGS typing data. The HLA alleles shared by both individuals suggest a putative extended haplotype: A∗25:01:01-C∗12:03:01-B∗18:01:01-DRB1∗15new-DRB5∗01:01:01-DQA1∗01:02:01-DQB1∗06:02:01-DPA1∗01:03:01-DPB1∗23:01:01. NGS typing solved the missing allele mystery through identification of a truncated DRB1∗15 allele comprising an exon 1 sequence but without exons 2, 3, or 4. Similarly, there is DRB4∗03:01N which has an exon 3 sequence of a DRB4∗01:01, but without an exon 2 sequence. These unusual alleles appear to be the results of historic multi-exon deletion events and add to the astounding diversity of the human major histocompatibility complex. Download high-res image (242KB) Download full-size image A.G. Smith: 2. Consultant; Company/Organization; Scisco Genetics Inc. S.E. Pereira: 4. Scientific/Medical Advisor; Company/Organization; Scisco Genetics Inc. C. Pyo: 4. Scientific/Medical Advisor; Company/Organization; Scisco Genetics Inc. W. Nelson: 5. Employee; Company/Organization; Scisco Genetics Inc. M.Z. Askar: 3. Speaker’s Bureau; Company/Organization; Immucor. 4. Scientific/Medical Advisor; Company/Organization; Illumina. D.E. Geraghty: 6. Stock Shareholder; Company/Organization; Scisco Genetics Inc.

Aim Most laboratories providing chimerism testing use electrophoretic analysis of STR loci or qPCR of SNP polymorphisms. STR assays are limited to 1–5% sensitivity and qPCR requires substantial amounts of DNA which may not be feasible in patients with low blood cell counts or for analysis of rare cell subsets. We developed a chimerism assay based on NGS of SNP and InDel polymorphisms and validated it in a clinical transplant immunology lab supporting a large HCT program. Methods Multiple polymorphic loci were evaluated for specificity, sensitivity and accuracy using artificial admixtures as well as direct comparison to qPCR results from patient specimens post HCT. An initial panel comprised 37 SNPs on 18 chromosomes and 12 InDels on 10 chromosomes. Target generation is performed in 2 multiplexed PCRs with 5 ng sample DNA per reaction. All NGS benchwork is accomplished within 6 h, followed by a 7 h MiSeq run, so that results are available for reporting early on day 2. Results Initial NGS testing used artificial admixtures of unrelated individuals, with mixtures from 10% to 0.1%, see Table 1. On average, 30 informative markers were identified between unrelated individuals and NGS achieved 0.5% sensitivity among all 4 admixture sets. Table 2 shows the results for NGS versus qPCR for 7 patient post HCT specimens. Download : Download high-res image (334KB) Download : Download full-size image Download : Download high-res image (247KB) Download : Download full-size image Conclusions These preliminary results show that NGS technology can provide accurate, informative, and sensitive detection of a minority species with minimal DNA quantity requirements, rapid turnaround and minimal hands on time. As laboratories implement NGS technology for high resolution genotyping of HLA and other genetic loci, extension to engraftment monitoring might also offer workplace efficiencies. M.Z. Askar: 3. Speaker’s Bureau; Company/Organization; Immucor. 4. Scientific/Medical Advisor; Company/Organization; Illumina. S.E. Pereira: 4. Scientific/Medical Advisor; Company/Organization; Scisco Genetics Inc. A.G. Smith: 2. Consultant; Company/Organization; Scisco Genetics Inc. C. Pyo: 4. Scientific/Medical Advisor; Company/Organization; Scisco Genetics Inc. W. Nelson: 5. Employee; Company/Organization; Scisco Genetics Inc. D.E. Geraghty: 6. Stock Shareholder; Company/Organization; Scisco Genetics Inc.

Aim Many laboratories use a 2-tier HLA typing process: a first pass intermediate resolution and then high resolution, when clinically necessary. SSP or qPCR provide rapid typing for deceased donor workup; SSOP is widely employed for higher volumes; and Sanger sequencing has been the gold standard for high resolution. However, SSOP and Sanger SBT often yield ambiguous results and resolution is expensive and time consuming. Next generation sequencing offers a single pass technology to achieve unambiguous HLA allele assignments. We compared commercial SSOP and NGS systems with respect to accuracy, turnaround time, effort and resolution level. Methods Five laboratories submitted coded, blinded samples, previously typed by SSOP at each institute, to a separate lab for NGS of HLA-A, B, C at exons 1–7, DRB1, DRB3/4/5, DQA1, DQB1, DPB1 at exons 1–4, and DPA1 at exons 2–4. For up to 24 samples by SSOP or up to 48 samples by NGS, benchwork is completed by one technologist on day 1 with results available for reporting on day 2. Results At the SSOP resolution level, results were concordant except for 11 SSOP assignments in 8 specimens due to false probe reactions at DRB1, DRB5, DQA1, DQB1, and DPB1. NGS identified 21 novel sequences: one with a multi-exon deletion and 20 with SNP polymorphisms in HLA-C, DPA1, DPB1, DQA1, DRB1, DRB3, DRB4, and DRB5 alleles. Across the highly polymorphic HLA-A, B, C, DRB1 loci, only 1% of intermediate resolution, IR, SSOP results were unambiguous. Even higher resolution, HR, SSOP by 1 lab gave only 17% specific allele assignments. In contrast, over 99% of NGS results were specific unambiguous genotypes. Across all loci, NGS typing was specific except for certain discrete diploid ambiguities, also found in SSOP. Conclusions This study provides a compelling rationale for implementing NGS for single pass HLA analysis with accurate, 2 day turnaround, which includes the high resolution, unambiguous genotyping critical for unrelated donor HCT and that may be required for sensitized patients with allele specific antibodies. A.G. Smith: 2. Consultant; Company/Organization; Scisco Genetics Inc. S.E. Pereira: 4. Scientific/Medical Advisor; Company/Organization; Scisco Genetics Inc. C. Pyo: 4. Scientific/Medical Advisor; Company/Organization; Scisco Genetics Inc. W. Nelson: 5. Employee; Company/Organization; Scisco Genetics Inc. M. Bettinotti: 3. Speaker’s Bureau; Company/Organization; One Lambda ThermoFisher. M.Z. Askar: 3. Speaker’s Bureau; Company/Organization; Immucor. 4. Scientific/Medical Advisor; Company/Organization; Illumina. D.E. Geraghty: 6. Stock Shareholder; Company/Organization; Scisco Genetics Inc. Download : Download high-res image (283KB) Download : Download full-size image

This paper combines new experimental data for electrokinetic characterization of hydrophobic polymers with a detailed discussion of the putative origins of charge at water-hydrophobe interfaces. Complexities in determining the origin of charge are discussed in the context of design and modeling challenges for electrokinetic actuation in hydrophobic microfluidic devices with aqueous working fluids. Measurements of interfacial charge are complicated by slip and interfacial water structuring phenomena (see Part 2, this issue). Despite these complexities, it is shown that (i) several hydrophobic materials, such as Teflon and Zeonor, have predictable electrokinetic properties and (ii) electrokinetic data for hydrophobic microfluidic systems is most consistent with the postulate that hydroxyl ion adsorption is the origin of charge.

Rare cells, such as circulating tumor cells (CTCs), can be heterogeneous. The isolation and identification of rare cells with different phenotypes is desirable, for clinical and biological applications. However, CTCs exist in a complex biological environment, which complicates the isolation and identification of particular subtypes. To address this need, we re-designed our ensemble-decision aliquot ranking (eDAR) system to detect, isolate, and study two subpopulations of rare cells in the same microchip. With this dual-capture eDAR device, we simultaneously and selectively isolated two subsets of CTCs from the same blood sample: One set expressed epithelial markers and the other had mesenchymal characteristics. We could apply other selection schemes with different sorting logics to isolate the two subpopulations on demand. The average recovery rate for each subpopulation was higher than 88% with a nearly 100% selectivity of the targeted cells; the throughput was 50 μL min(-1).

Aim The practice of using genetic information as guidance for clinical application, so called precision medicine, has been in use for over 30 years in donor and recipient matching for HLA in hematopoietic cell transplantation. As precision medicine moves into the mainstream of clinical practice, a driving force is the availability of novel technologies and the creation of population datasets that can inform the details of genetic variation at immune response loci. Among the most polymorphic loci in the human genome are HLA class I and class II, MICA/B and KIR gene families. These genes are central to the immune response, which in turn is central to most common diseases. We are using resources from the 1000 Genome Project to rigorously evaluate a novel next generation genotyping protocol, to refine existing 1000 genome data resources for population and data mining studies, and to supplement currently available HLA and immune response genetic data sets. Methods The 1000 Genomes Project, one of the largest public catalogues of human variation and genotype data, provides panels for additional studies, comprising 2,542 DNA samples from 26 ethnic populations available through the International Genome Sample Resource. We are using a novel and extensible next generation sequencing protocol for genotyping of HLA, MICA/B and KIR. Results To date, 800 samples have been fully genotyped for HLA, MICA/B and KIR. The data are examined to identify allele groups and haplotypes that define each of the 26 populations. HLA class I intron sequence variation between populations is examined for potential relevance in the transplant setting and in disease association studies in general. Once published all data will be deposited in publically accessible databases. Conclusions This study demonstrates that novel genotyping methods can be used to acquire the detail of the genetics of the immune response sufficient for application in precision medicine.

Current high-resolution HLA typing technologies frequently produce ambiguous results that mandate extended testing prior to reporting. Through multiplex sequencing of individual amplicons from many individuals at multiple loci, next generation sequencing (NGS) promises to eliminate heterozygote ambiguities and extend the breadth of genetic data acquired with little additional effort. We report here on assessment of a novel NGS HLA genotyping system for resequencing exons 2 and 3 of DRB1/B3/B4/B5, DQA1 and DQB1 and exon 2 of DPA1 and DPB1 on the MiSeq platform. In a cohort of 2605 hematopoietic cell transplant recipients and donors, NGS achieved 99.6% accuracy for DRB1 allele assignments and 99.5% for DQB1, compared to legacy genotypes generated pretransplant. NGS provided at least single 4-digit allele resolution for 97% of genotypes at DRB1 and 100% at DQB1. Overall, NGS typing identified 166 class II alleles, including 9 novel sequences with greater than 99% accuracy for DRB1 and DQB1 genotypes and elimination of diploid ambiguities through in-phase sequencing demonstrated the robust reliability of the NGS HLA genotyping reagents and analysis software employed in this study.

By designing and implementing a new experimental method, we have measured the dynamic advancing and receding contact angles and the resulting hysteresis of droplets under electrowetting-on-dielectric (EWOD). Measurements were obtained over wide ranges of applied EWOD voltages, or electrowetting numbers (0 ≤ Ew ≤ 0.9), and droplet sliding speeds, or capillary numbers (1.4 × 10(-5) ≤ Ca ≤ 6.9 × 10(-3)). If Ew or Ca is low, dynamic contact angle hysteresis is not affected much by the EWOD voltage or the sliding speed; that is, the hysteresis increases by less than 50% with a 2 order-of-magnitude increase in sliding speed when Ca10(-3). If both Ew and Ca are high, however, the hysteresis increases with either the EWOD voltage or the sliding speed. Stick-slip oscillations were observed at Ew0.4. Data are interpreted with simplified hydrodynamic (Cox-Voinov) and molecular-kinetic theory (MKT) models; the Cox-Voinov model captures the trend of the data, but it yields unreasonable fitting parameters. MKT fitting parameters associated with the advancing contact line are reasonable, but a lack of symmetry indicates that a more intricate model is required.

We are developing new electrowetting-on-dielectric (EWOD) digital microfluidic systems for operating at non-atmospheric conditions. The first generation is a compact pressure chamber with an electric feed-through, enabling EWOD operation within a gaseous medium of well-controlled pressure and composition. EWOD performance is insensitive to chamber pressure because the chip is of open-channel architecture. We demonstrate two different types of previously unachievable processes - (i) controlling evaporation rates of common solvents (water, methanol, acetonitrile) by adjusting the pressure of an inert gaseous medium (N 2 ), and (ii) controlling the reaction rate of a solid-liquid-gas-phase reaction by adjusting the pressure of a gas-phase reagent (H 2 ).

We present a miniature system for generating and measuring liquid microfilaments for capillary breakup rheometry. The key component is a chip that splits samples in open air, creating shear-free liquid threads that can be measured by optical micrometry. For testing polar samples, electrowetting-on-dielectric (EWOD) is used to induce spreading, which causes necking and capillary instability-driven breakup. Low-surface-tension samples spread spontaneously, and thus reach instability without EWOD. We use LED optical micrometry to measure inelastic and elastic microfilaments, and the results are consistent with capillary breakup theory and comparable to those obtained by established experimental methods.

We report an experimental investigation of the resistive forces imparted on droplets actuated by electrowetting-on-dielectric (EWOD). While the advancing contact angle is always larger than the receding of a droplet moving on a solid surface under conventional actuation means, EWOD actuation is unique because the advancing angle is smaller than the receding. We recorded high-speed videos of sliding droplets under electrowetting to elucidate this seemingly paradoxical contact angle hysteresis. The results indicate a transition point at Ca≈ 10−3, after which the dominant resistance force becomes strongly speed-and voltage-dependent.

We present a microfluidic chip for multiplex thermal processing of discrete micro- and nano-liter sample droplets driven by electrowetting-on-dielectric (EWOD). The system features local temperature control integrated on chip in addition to the basic fluidic functionalities previously reported for EWOD devices [1]. Multifunctioning indium-tin-oxide (ITO) electrodes serve as optically transparent resistive heaters, temperature sensors, and EWOD actuation pads. With a 1 ?L sample, heaters reach programmed set points in a few seconds and stabilize to ±1 °C. We demonstrate automated on-chip proteomics sample processing and direct characterization by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). The results, showing increased insulin disulfide reduction efficiency with heater temperatures from 22 to 130 °C, highlight the efficacy of the chip.

Aim Current technologies for analysis of complex polymorphic gene systems restrict the ability to routinely obtain both breadth (number of loci) and depth (allele resolution) of data. The costs of increasing the breadth of analysis are additive in that the cost for each locus is similar. The costs for high resolution analysis of highly polymorphic genes, such as HLA, are increased by the extended processes required to resolve ambiguous heterozygous typing results. Methods In order to improve the economy of obtaining both broad and high-resolution data in both high and medium throughput settings, we have undertaken to develop next generation sequencing (NGS) reagents and software systems for analysis of complex immune genes using the Illumina MiSeq device. For the HLA complex, our original software extracts precise HLA typings from highly multiplexed raw NGS data by aligning the uniquely barcoded sequence fragments followed by analysis with an HLA allele calling script. Data for HLA-A, B, C, exons 2, 3, and 4 are obtained with phase determined between exons 2 and 3 by sequencing and with exon 4 by coincidence with established databases. Data for DRB1345, DQA1, DQB1, DPB1 are obtained from exons 2 and 3 with phase between exons determined by coincidence with established databases. DPA1 data are obtained from exon 2. We also developed an NGS KIR haplotyping system and are evaluating SNP-based chimerism analysis, both with workflows similar to the HLA approach. Results Beyond extensive in-house evaluation, we took our HLA system to two clinical laboratories associated with hematopoietic cell transplant programs for beta testing of our NGS approach in moderate throughput environments. Conclusions We discuss these results and the proven enhanced efficacy and economy of the NGS typing approach in moderate throughput laboratories. Furthermore, we discuss future NGS applications that will become available to those laboratories to support their evolving role in the application of precision medicine.

We present a microfluidic platform for the formation and electrical measurement of lipid bilayer membranes. Using electrowetting on dielectric (EWOD), two or more aqueous droplets surrounded by a lipid-containing organic phase were manipulated into contact to form a lipid bilayer at their interface. Thin-film Ag/AgCl electrodes integrated into the device enabled electrical measurement of membrane formation and the incorporation of gramicidin channels of two bilayers in parallel.