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The SARS-CoV-2 pandemic has differentially impacted populations across race and ethnicity. A multi-omic approach represents a powerful tool to examine risk across multi-ancestry genomes. We leverage a pandemic tracking strategy in which we sequence viral and host genomes and transcriptomes from nasopharyngeal swabs of 1049 individuals (736 SARS-CoV-2 positive and 313 SARS-CoV-2 negative) and integrate them with digital phenotypes from electronic health records from a diverse catchment area in Northern California. Genome-wide association disaggregated by admixture mapping reveals novel COVID-19-severity-associated regions containing previously reported markers of neurologic, pulmonary and viral disease susceptibility. Phylodynamic tracking of consensus viral genomes reveals no association with disease severity or inferred ancestry. Summary data from multiomic investigation reveals metagenomic and HLA associations with severe COVID-19. The wealth of data available from residual nasopharyngeal swabs in combination with clinical data abstracted automatically at scale highlights a powerful strategy for pandemic tracking, and reveals distinct epidemiologic, genetic, and biological associations for those at the highest risk., (© 2022. The Author(s).)

Next generation sequencing (NGS) is being applied for HLA typing in research and clinical settings. NGS HLA typing has made it feasible to sequence exons, introns and untranslated regions simultaneously, with significantly reduced labor and reagent cost per sample, rapid turnaround time, and improved HLA genotype accuracy. NGS technologies bring challenges for cost-effective computation, data processing and exchange of NGS-based HLA data. To address these challenges, guidelines and specifications such as Genotype List (GL) String, Minimum Information for Reporting Immunogenomic NGS Genotyping (MIRING), and Histoimmunogenetics Markup Language (HML) were proposed to streamline and standardize reporting of HLA genotypes. As part of the 17th International HLA and Immunogenetics Workshop (IHIW), we implemented standards and systems for HLA genotype reporting that included GL String, MIRING and HML, and found that misunderstanding or misinterpretations of these standards led to inconsistencies in the reporting of NGS HLA genotyping results. This may be due in part to a historical lack of centralized data reporting standards in the histocompatibility and immunogenetics community. We have worked with software and database developers, clinicians and scientists to address these issues in a collaborative fashion as part of the Data Standard Hackathons (DaSH) for NGS. Here we report several categories of challenges to the consistent exchange of NGS HLA genotyping data we have observed. We hope to address these challenges in future DaSH for NGS efforts., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.)

Multiple sclerosis (MS) susceptibility shows strong genetic associations with HLA alleles and haplotypes. We genotyped 11 HLA genes in 477 non-Hispanic European MS patients and their 954 unaffected parents using a validated next-generation sequencing (NGS) methodology. HLA haplotypes were assigned unequivocally by tracing HLA allele transmissions. We explored HLA haplotype/allele associations with MS using the genotypic transmission disequilibrium test (gTDT) and multiallelic TDT (mTDT). We also conducted a case-control (CC) study with all patients and 2029 healthy unrelated ethnically matched controls. We performed separate analyses of 54 extended multi-case families by reviewing transmission of haplotype blocks. The haplotype fragment including DRB5*01:01:01~DRB1*15:01:01:01 was significantly associated with predisposition (gTDT: p < 2.20e-16; mTDT: p =1.61e-07; CC: p < 2.22e-16) as reported previously. A second risk allele, DPB1*104:01 (gTDT: p = 3.69e-03; mTDT: p = 2.99e-03; CC: p = 1.00e-02), independent from the haplotype bearing DRB1*15:01 was newly identified. The allele DRB1*01:01:01 showed significant protection (gTDT: p = 8.68e-06; mTDT: p = 4.50e-03; CC: p = 1.96e-06). Two DQB1 alleles, DQB1*03:01 (gTDT: p = 2.86e-03; mTDT: p = 5.56e-02; CC: p = 4.08e-05) and DQB1*03:03 (gTDT: p = 1.17e-02; mTDT: p = 1.16e-02; CC: p = 1.21e-02), defined at two-field level also showed protective effects. The HLA class I block, A*02:01:01:01~C*03:04:01:01~B*40:01:02 (gTDT: p = 5.86e-03; mTDT: p = 3.65e-02; CC: p = 9.69e-03) and the alleles B*27:05 (gTDT: p = 6.28e-04; mTDT: p = 2.15e-03; CC: p = 1.47e-02) and B*38:01 (gTDT: p = 3.20e-03; mTDT: p = 6.14e-03; CC: p = 1.70e-02) showed moderately protective effects independently from each other and from the class II associated factors. By comparing statistical significance of 11 HLA loci and 19 haplotype segments with both untruncated and two-field allele names, we precisely mapped MS candidate alleles/haplotypes while eliminating false signals resulting from 'hitchhiking' alleles. We assessed genetic burden for the HLA allele/haplotype identified in this study. This family-based study including the highest-resolution of HLA alleles proved to be powerful and efficient for precise identification of HLA genotypes associated with both, susceptibility and protection to development of MS., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Osoegawa, Creary, Montero-Martín, Mallempati, Gangavarapu, Caillier, Santaniello, Isobe, Hollenbach, Hauser, Oksenberg and Fernández-Viňa.)

During COVID19 and other viral pandemics, rapid generation of host and pathogen genomic data is critical to tracking infection and informing therapies. There is an urgent need for efficient approaches to this data generation at scale. We have developed a scalable, high throughput approach to generate high fidelity low pass whole genome and HLA sequencing, viral genomes, and representation of human transcriptome from single nasopharyngeal swabs of COVID19 patients.

Here we studied HLA blocks and haplotypes in a group of 218 Lacandon Maya Native American using a high-resolution next generation sequencing (NGS) method. We assessed the genetic diversity of HLA class I and class II in this population, and determined the most probable ancestry of Lacandon Maya HLA class I and class II haplotypes. Importantly, this Native American group showed a high degree of both HLA homozygosity and linkage disequilibrium across the HLA region and also lower class II HLA allelic diversity than most previously reported populations (including other Native American groups). Distinctive alleles present in the Lacandon population include HLA-A*24:14 and HLA-B*40:08. Furthermore, in Lacandons we observed a high frequency of haplotypes containing the allele HLA-DRB1*04:11, a relatively frequent allele in comparison with other neighboring indigenous groups. The specific demographic history of the Lacandon population including inbreeding, as well as pathogen selection, may have elevated the frequencies of a small number of HLA class II alleles and DNA blocks. To assess the possible role of different selective pressures in determining Native American HLA diversity, we evaluated the relationship between genetic diversity at HLA-A, HLA-B and HLA-DRB1 and pathogen richness for a global dataset and for Native American populations alone. In keeping with previous studies of such relationships we included distance from Africa as a covariate. After correction for multiple comparisons we did not find any significant relationship between pathogen diversity and HLA genetic diversity (as measured by polymorphism information content) in either our global dataset or the Native American subset of the dataset. We found the expected negative relationship between genetic diversity and distance from Africa in the global dataset, but no relationship between HLA genetic diversity and distance from Africa when Native American populations were considered alone.

The human leukocyte antigen (HLA) genes are extremely polymorphic and are useful molecular markers to make inferences about human population history. However, the accuracy of the estimation of genetic diversity at HLA loci very much depends on the technology used to characterize HLA alleles; high-resolution genotyping of long-range HLA gene products improves the assessment of HLA population diversity as well as other population parameters compared to lower resolution typing methods. In this study we examined allelic and haplotype HLA diversity in a large healthy European American population sourced from the UCSF-DNA bank. A high-resolution next-generation sequencing method was applied to define non-ambiguous 3- and 4-field alleles at the HLA-A, HLA-C, HLA-B, HLA-DRB1, HLA-DRB3/4/5, HLA-DQA1, HLA-DQB1, HLA-DPA1, and HLA-DPB1 loci in samples provided by 2248 unrelated individuals. A number of population parameters were examined including balancing selection and various measurements of linkage disequilibrium were calculated. There were no detectable deviations from Hardy-Weinberg proportions at HLA-A, HLA-DRB1, HLA-DQA1 and HLA-DQB1. For the remaining loci moderate and significant deviations were detected at HLA-C, HLA-B, HLA-DRB3/4/5, HLA-DPA1 and HLA-DPB1 loci mostly from population substructures. Unique 4-field associations were observed among alleles at 2 loci and haplotypes extending large intervals that were not apparent in results obtained using testing methodologies with limited sequence coverage and phasing. The high diversity at HLA-DPA1 results from detection of intron variants of otherwise well conserved protein sequences. It may be speculated that divergence in exon sequences may be negatively selected. Our data provides a valuable reference source for future population studies that may allow for precise fine mapping of coding and non-coding sequences determining disease susceptibility and allo-immunogenicity., (Copyright © 2019 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.)

The 17th International HLA and Immunogenetics Workshop (IHIW) conducted a project entitled "The Study of Haplotypes in Families by NGS HLA". We investigated the HLA haplotypes of 1017 subjects in 263 nuclear families sourced from five US clinical immunogenetics laboratories, primarily as part of the evaluation of related donor candidates for hematopoietic stem cell and solid organ transplantation. The parents in these families belonged to five broad groups - African (72 parents), Asian (115), European (210), Hispanic (118) and "Other" (11). High-resolution HLA genotypes were generated for each subject using next-generation sequencing (NGS) HLA typing systems. We identified the HLA haplotypes in each family using HaplObserve, software that builds haplotypes in families by reviewing HLA allele segregation from parents to children. We calculated haplotype frequencies within each broad group, by treating the parents in each family as unrelated individuals. We also calculated standard measures of global linkage disequilibrium (LD) and conditional asymmetric LD for each ethnic group, and used untruncated and two-field allele names to investigate LD patterns. Finally we demonstrated the utility of consensus DNA sequences in identifying novel variants, confirming them using HLA allele segregation at the DNA sequence level., (Copyright © 2019 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.)

Extended molecular characterization of HLA genes in the IHWG reference B-lymphoblastoid cell lines (B-LCLs) was one of the major goals for the 17th International HLA and Immunogenetics Workshop (IHIW). Although reference B-LCLs have been examined extensively in previous workshops complete high-resolution typing was not completed for all the classical class I and class II HLA genes. To address this, we conducted a single-blind study where select panels of B-LCL genomic DNA samples were distributed to multiple laboratories for HLA genotyping by next-generation sequencing methods. Identical cell panels comprised of 24 and 346 samples were distributed and typed by at least four laboratories in order to derive accurate consensus HLA genotypes. Overall concordance rates calculated at both 2- and 4-field allele-level resolutions ranged from 90.4% to 100%. Concordance for the class I genes ranged from 91.7 to 100%, whereas concordance for class II genes was variable; the lowest observed at HLA-DRB3 (84.2%). At the maximum allele-resolution 78 B-LCLs were defined as homozygous for all 11 loci. We identified 11 novel exon polymorphisms in the entire cell panel. A comparison of the B-LCLs NGS HLA genotypes with the HLA genotypes catalogued in the IPD-IMGT/HLA Database Cell Repository, revealed an overall allele match at 68.4%. Typing discrepancies between the two datasets were mostly due to the lower-resolution historical typing methods resulting in incomplete HLA genotypes for some samples listed in the IPD-IMGT/HLA Database Cell Repository. Our approach of multiple-laboratory NGS HLA typing of the B-LCLs has provided accurate genotyping data. The data generated by the tremendous collaborative efforts of the 17th IHIW participants is useful for updating the current cell and sequence databases and will be a valuable resource for future studies., (Copyright © 2019. Published by Elsevier Inc.)

Next-generation sequencing (NGS) at the HLA-A, -B, -C, -DPA1, -DPB1, -DQA1, -DQB1, -DRB1 and -DRB3/4/5 loci was performed on 282 healthy unrelated individuals from different major regions of Spain. High-resolution HLA genotypes defined by full sequencing of class I loci and extended coverage of class II loci were obtained to determine allele frequencies and also to estimate extended haplotype frequencies. HLA alleles were typed at the highest resolution level (4-field level, 4FL); with exception of a minor deviation in HLA-DPA1, no statistically significant deviations from expected Hardy Weinberg Equilibrium (HWE) proportions were observed for all other HLA loci. This study provides new 4FL-allele and -haplotype frequencies estimated for the first time in the Spanish population. Furthermore, our results describe extended haplotypes (including the less frequently typed HLA-DPA1 and HLA-DQA1 loci) and show distinctive haplotype associations found at 4FL-allele definition in this Spanish population study. The distinctive allelic and haplotypic diversity found at the 4FL reveals the high level of heterozygosity and specific haplotypic associations displayed that were not apparent at 2-field level (2FL). Overall, these results may contribute as a useful reference source for future population studies, for HLA-disease association studies as a healthy control group dataset and for improving donor recruitment strategies of bone marrow registries. HLA genotyping data of this Spanish population cohort was also included in the 17th International Histocompatibility and Immunogenetics Workshop (IHIW) as part of the study of HLA diversity in unrelated worldwide populations using NGS., (Copyright © 2019 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.)

Background: The association between HLA-DRB1*15:01 with multiple sclerosis (MS) susceptibility is well established, but the contribution of the tightly associated HLA-DRB5*01:01 allele has not yet been completely ascertained. Similarly, the effects of HLA-DRB1*04:01 alleles and haplotypes, defined at the full-gene resolution level with MS risk remains to be elucidated., Objectives: To characterize the molecular architecture of class II HLA-DR15 and HLA-DR4 haplotypes associated with MS., Methods: Next-generation sequencing was used to determine HLA-DQB1, HLA-DQA1, and HLA-DRB1/4/5 alleles in 1403 unrelated European-American patients and 1425 healthy unrelated controls. Effect sizes of HLA alleles and haplotypes on MS risk were measured by odds ratio (OR) with 95% confidence intervals., Results: HLA-DRB1*15:01:01:01SG (OR = 3.20, p < 2.2E-16), HLA-DRB5*01:01:01 (OR = 2.96, p < 2.2E-16), and HLA-DRB5*01:01:01v1&#95;STR1 (OR = 8.18, p = 4.3E-05) alleles all occurred at significantly higher frequencies in MS patients compared to controls. The most significant predis-posing haplotypes were HLA-DQB1*06:02:01~ HLA-DQA1*01:02:01:01SG~HLA-DRB1*15:01:01:01SG~HLA-DRB5*01:01:01 and HLA-DQB1*06:02:01~HLA-DQA1*01:02:01:01SG~HLA-DRB1*15:01:01:01SG~HLA-DRB5*01:01:01v1&#95;STR1 (OR = 3.19, p < 2.2E-16; OR = 9.30, p = 9.7E-05, respectively). Analyses of the HLA-DRB1*04 cohort in the absence of HLA-DRB1*15:01 haplotypes revealed that the HLA-DQB1*03:01:01:01~HLA-DQA1*03:03:01:01~HLA-DRB1*04:01:01:01SG~HLA-DRB4*01:03:01:01 haplotype was protective (OR = 0.64, p = 0.028), whereas the HLA-DQB1*03:02:01~HLA-DQA1*03:01:01~HLA-DRB1*04:01:01:01SG~HLA-DRB4*01:03:01:01 haplotype was associated with MS susceptibility (OR = 1.66, p = 4.9E-03)., Conclusion: HLA-DR15 haplotypes, including genomic variants of HLA-DRB5, and HLA-DR4 haplotypes affect MS risk.

The 17th International HLA and Immunogenetics Workshop (IHIW) organizers conducted a Pilot Study (PS) in which 13 laboratories (15 groups) participated to assess the performance of the various sequencing library preparation protocols, NGS platforms and software in use prior to the workshop. The organizers sent 50 cell lines to each of the 15 groups, scored the 15 independently generated sets of NGS HLA genotyping data, and generated "consensus" HLA genotypes for each of the 50 cell lines. Proficiency Testing (PT) was subsequently organized using four sets of 24 cell lines, selected from 48 of 50 PS cell lines, to validate the quality of NGS HLA typing data from the 34 participating IHIW laboratories. Completion of the PT program with a minimum score of 95% concordance at the HLA-A, HLA-B, HLA-C, HLA-DRB1 and HLA-DQB1 loci satisfied the requirements to submit NGS HLA typing data for the 17th IHIW projects. Together, these PS and PT efforts constituted the 17th IHIW Quality Control project. Overall PT concordance rates for HLA-A, HLA-B, HLA-C, HLA-DPA1, HLA-DPB1, HLA-DQA1, HLA-DQB1, HLA-DRB1, HLA-DRB3, HLA-DRB4 and HLA-DRB5 were 98.1%, 97.0% and 98.1%, 99.0%, 98.6%, 98.8%, 97.6%, 96.0%, 99.1%, 90.0% and 91.7%, respectively. Across all loci, the majority of the discordance was due to allele dropout. The high cost of NGS HLA genotyping per experiment likely prevented the retyping of initially failed HLA loci. Despite the high HLA genotype concordance rates of the software, there remains room for improvement in the assembly of more accurate consensus DNA sequences by NGS HLA genotyping software., (Copyright © 2019 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.)

Background: Variant discovery for rare genetic diseases using Illumina genome or exome sequencing involves screening of up to millions of variants to find only the one or few causative variant(s). Sequencing or alignment errors create "false positive" variants, which are often retained in the variant screening process. Methods to remove false positive variants often retain many false positive variants. This report presents VarBin, a method to prioritize variants based on a false positive variant likelihood prediction., Methods: VarBin uses the Genome Analysis Toolkit variant calling software to calculate the variant-to-wild type genotype likelihood ratio at each variant change and position divided by read depth. The resulting Phred-scaled, likelihood-ratio by depth (PLRD) was used to segregate variants into 4 Bins with Bin 1 variants most likely true and Bin 4 most likely false positive. PLRD values were calculated for a proband of interest and 41 additional Illumina HiSeq, exome and whole genome samples (proband's family or unrelated samples). At variant sites without apparent sequencing or alignment error, wild type/non-variant calls cluster near -3 PLRD and variant calls typically cluster above 10 PLRD. Sites with systematic variant calling problems (evident by variant quality scores and biases as well as displayed on the iGV viewer) tend to have higher and more variable wild type/non-variant PLRD values. Depending on the separation of a proband's variant PLRD value from the cluster of wild type/non-variant PLRD values for background samples at the same variant change and position, the VarBin method's classification is assigned to each proband variant (Bin 1 to Bin 4)., Results: To assess VarBin performance, Sanger sequencing was performed on 98 variants in the proband and background samples. True variants were confirmed in 97% of Bin 1 variants, 30% of Bin 2, and 0% of Bin 3/Bin 4., Conclusions: These data indicate that VarBin correctly classifies the majority of true variants as Bin 1 and Bin 3/4 contained only false positive variants. The "uncertain" Bin 2 contained both true and false positive variants. Future work will further differentiate the variants in Bin 2.

Targeted FISH analysis is an essential component of the management of plasma cell myeloma for identification of cytogenetic abnormalities. The purpose of this study was to evaluate the column-free method, RoboSep® (RS), for sorting CD138-expressing cells in bone marrow aspirates. Comparative analysis of column-based and RS methodologies was carried out on 54 paired bone marrow aspirate validation samples from patients undergoing work-up for plasma cell dyscrasia. Abnormalities detected by FISH analysis using an IGH@/CCND1 probe set were seen in 54% with RS, and 44% with column-based. We found a statistically significant difference between the yield of abnormalities detected in paired positive cases (p = 0.0001). An additional 183 consecutive post-validation samples sorted by RS showed recurrent genetic abnormalities in 85/120 (71%) of successfully sorted samples with ≥ 1% plasma cells but in none of 63 samples in which FISH analysis was completed on samples that could not be sorted due to insufficient plasma cells upon cell sorting. The column-free method successfully sorted PC, when present in ≥ 1% of cells, for detection of abnormalities by FISH. Furthermore, our data suggest that FISH analysis should not be performed on samples with an inadequate yield at the cell selection step.