Genotype Calls Research Articles

Sequencing of genes of drug response in tumor DNA and implications for precision medicine in cancer patients.

Tumor DNA sequencing is becoming standard-of-care for patient treatment decisions. We evaluated genotype concordance between tumor DNAand genomic DNA from blood and catalogued functional effects of somatic mutations in 21 drug response genes in 752 solid tumor patients. Using a threshold of 10% difference between tumor and blood DNA variant allele fraction (VAF), concordance for heterogenous genotype calls was 78%and increased to 97.5% using a 30% VAFthreshold. Somatic mutations were observed in all 21 drug response genes, and 44% of patients had at least one somatic mutation in these genes. In tumor DNA, eight patients had a frameshift mutation in CYP2C8, which metabolizes taxanes. Overall, somatic copy number losses were more frequent than gains, including for CYP2C19 and CYP2D6 which had the most frequent copy number losses. However, copy number gains in TPMT were more than four times as common as losses. Seven % of patients had copy number gains in ABCB1, a multidrug resistance transporter of anti-cancer agents. These results demonstrate tumor-only DNA sequencing might not be reliable to call germline genotypes of drug response variants.

Pf7: an open dataset of Plasmodium falciparum genome variation in 20,000 worldwide samples.

We describe the MalariaGEN Pf7 data resource, the seventh release of Plasmodium falciparum genome variation data from the MalariaGEN network. It comprises over 20,000 samples from 82 partner studies in 33 countries, including several malaria endemic regions that were previously underrepresented. For the first time we include dried blood spot samples that were sequenced after selective whole genome amplification, necessitating new methods to genotype copy number variations. We identify a large number of newly emerging crt mutations in parts of Southeast Asia, and show examples of heterogeneities in patterns of drug resistance within Africa and within the Indian subcontinent. We describe the profile of variations in the C-terminal of the csp gene and relate this to the sequence used in the RTS,S and R21 malaria vaccines. Pf7 provides high-quality data on genotype calls for 6 million SNPs and short indels, analysis of large deletions that cause failure of rapid diagnostic tests, and systematic characterisation of six major drug resistance loci, all of which can be freely downloaded from the MalariaGEN website.

Modifications of Kompetitive Allele-Specific PCR (KASP) Genotyping for Detection of Rare Alleles.

KASP is commonly used to genotype bi-allelic SNPs and In/Dels, and the standard protocol works well when both alleles are nearly equally prevalent in the DNA template. To detect rare alleles in bulked samples or to distinguish more than three genotypes, such as tri-allelic loci or mutations across orthologous genes in polyploids, adjustments to the protocol and/or data analysis are required. In this chapter, we present modified protocols for these non-traditional applications, including reaction conditions that enhance the fluorophore signal from rare alleles, resulting in increased KASP assay sensitivity. We also describe alternative KASP data analysis approaches that increase statistical certainty of genotyping calls. Furthermore, this increased assay sensitivity enables high-throughput genotyping using KASP, as samples can be pooled and tested in a single reaction. For example, rare alleles can be detected in mixed seed pools when present in ratios as low as 1 in 200. The assay modifications presented here expand the options available for complex genotyping, and retain KASP's advantages of being cheap, fast, and accurate.

Developing best practices for genotyping-by-sequencing analysis in the construction of linkage maps.

Genotyping-by-sequencing (GBS) provides affordable methods for genotyping hundreds of individuals using millions of markers. However, this challenges bioinformatic procedures that must overcome possible artifacts such as the bias generated by polymerase chain reaction duplicates and sequencing errors. Genotyping errors lead to data that deviate from what is expected from regular meiosis. This, in turn, leads to difficulties in grouping and ordering markers, resulting in inflated and incorrect linkage maps. Therefore, genotyping errors can be easily detected by linkage map quality evaluations. We developed and used the Reads2Map workflow to build linkage maps with simulated and empirical GBS data of diploid outcrossing populations. The workflows run GATK, Stacks, TASSEL, and Freebayes for single-nucleotide polymorphism calling and updog, polyRAD, and SuperMASSA for genotype calling, as well as OneMap and GUSMap to build linkage maps. Using simulated data, we observed which genotype call software fails in identifying common errors in GBS sequencing data and proposed specific filters to better handle them. We tested whether it is possible to overcome errors in a linkage map using genotype probabilities from each software or global error rates to estimate genetic distances with an updated version of OneMap. We also evaluated the impact of segregation distortion, contaminant samples, and haplotype-based multiallelic markers in the final linkage maps. Through our evaluations, we observed that some of the approaches produce different results depending on the dataset (dataset dependent) and others produce consistent advantageous results among them (dataset independent). We set as default in the Reads2Map workflows the approaches that showed to be dataset independent for GBS datasets according to our results. This reduces the number of required tests to identify optimal pipelines and parameters for other empirical datasets. Using Reads2Map, users can select the pipeline and parameters that best fit their data context. The Reads2MapApp shiny app provides a graphical representation of the results to facilitate their interpretation.

Population admixtures in medaka inferred by multiple arbitrary amplicon sequencing

Cost-effective genotyping can be achieved by sequencing PCR amplicons. Short 3–10 base primers can arbitrarily amplify thousands of loci using only a few primers. To improve the sequencing efficiency of the multiple arbitrary amplicon sequencing (MAAS) approach, we designed new primers and examined their efficiency in sequencing and genotyping. To demonstrate the effectiveness of our method, we applied it to examining the population structure of the small freshwater fish, medaka (Oryzias latipes). We obtained 2987 informative SNVs with no missing genotype calls for 67 individuals from 15 wild populations and three artificial strains. The estimated phylogenic and population genetic structures of the wild populations were consistent with previous studies, corroborating the accuracy of our genotyping method. We also attempted to reconstruct the genetic backgrounds of a commercial orange mutant strain, Himedaka, which has caused a genetic disturbance in wild populations. Our admixture analysis focusing on Himedaka showed that at least two wild populations had genetically been contributed to the nuclear genome of this mutant strain. Our genotyping methods and results will be useful in quantitative assessments of genetic disturbance by this commercially available strain.

Whole-genome sequencing of artificial single-nucleotide variants induced by DNA degradation in biological crime scene traces

The aim of this study was to identify artificial single-nucleotide variants (SNVs) in degraded trace DNA samples. In a preliminary study, blood samples were stored for up to 120 days and whole-genome sequencing was performed using the Snakemake workflow dna-seq-gatk-variant-calling to identify positions that vary between the time point 0 sample and the aged samples. In a follow-up study on blood and saliva samples stored under humid and dry conditions, potential marker candidates for the estimation of the age of a blood stain (= time since deposition) were identified. Both studies show that a general decrease in the mean fragment size of the libraries over time was observed, presumably due to the formation of abasic sites during DNA degradation which are more susceptible to strand breaks by mechanical shearing of DNA. Unsurprisingly, an increase in the number of failed genotype calls (no coverage) was detected over time. Both studies indicated the presence of artificial SNVs with the majority of changes happening at guanine and cytosine positions. This confirms previous studies and can be explained by depurination through hydrolytic attacks which more likely deplete guanine while deamination leads to cytosine to thymine variants. Even complete genotype switches from homozygote 0/0 genotypes to the opposite 1/1 genotypes were observed. While positions with such drastic changes might provide suitable candidate markers for estimating short-term time since deposition (TsD), 11 markers were identified which show a slower gradual change of the relative abundance of the artificial variant in both blood and saliva samples, irrespective of storage conditions.

Duet: SNP-assisted structural variant calling and phasing using Oxford nanopore sequencing

BackgroundWhole genome sequencing using the long-read Oxford Nanopore Technologies (ONT) MinION sequencer provides a cost-effective option for structural variant (SV) detection in clinical applications. Despite the advantage of using long reads, however, accurate SV calling and phasing are still challenging.ResultsWe introduce Duet, an SV detection tool optimized for SV calling and phasing using ONT data. The tool uses novel features integrated from both SV signatures and single-nucleotide polymorphism signatures, which can accurately distinguish SV haplotype from a false signal. Duet was benchmarked against state-of-the-art tools on multiple ONT sequencing datasets of sequencing coverage ranging from 8× to 40×. At low sequencing coverage of 8×, Duet performs better than all other tools in SV calling, SV genotyping and SV phasing. When the sequencing coverage is higher (20× to 40×), the F1-score for SV phasing is further improved in comparison to the performance of other tools, while its performance of SV genotyping and SV calling remains higher than other tools.ConclusionDuet can perform accurate SV calling, SV genotyping and SV phasing using low-coverage ONT data, making it very useful for low-coverage genomes. It has great performance when scaled to high-coverage genomes, which is adaptable to various clinical applications. Duet is open source and is available at https://github.com/yekaizhou/duet.

Evaluating probabilistic genotyping for low-pass DNA sequencing

Most genomic methods consider the sample genotype. Data are evaluated at some location, and if the signal strength is sufficient, a genotype call is made. Conversely, sites that lack sufficient signal are treated as missing data. Such methods for genotype calling are binary, and this dichotomy limits genomic analyses to relatively high-coverage (and high-cost) massively parallel sequencing (MPS) data. It follows that bioinformatic methods that rely on genotypes may not be ideal for trace DNA samples, such as those sometimes encountered in forensic investigations, but even when applicable such analyses can be expensive. However, there are some genomic analyses where having many uncertain genotypes (with measured uncertainty) assayed over the entirety of the genome may be more powerful than current multi-locus approaches that consider a limited number of well-characterized markers. Methods for such problems may rely on genotype likelihood, which expresses the likelihood of alternative genotype calls in addition to the most likely call. One application that can benefit from genotype likelihoods is kinship analysis. NgsRelate is a bioinformatic tool that infers pairwise relatedness using a probabilistic genotyping framework, which accommodates the uncertainty associated with genotype calls for low-pass MPS data. Here, NgsRelate was used to infer kinship coefficients from low-pass whole genome sequencing data from a known pedigree. Multiple samples in a titration series (ranging from 50 ng to 0.5 ng) on a single MPS S4 flow cell were assessed. A reproducible scientific bioinformatic workflow was developed to evaluate kinship coefficients considering up to 3rd degree relatives. NgsRelate was found to provide robust assessments of kinship. Further, the use of low-pass MPS data provides a more cost-effective way to conduct forensic investigations.

Whole-genome sequencing of degraded DNA for investigative genetic genealogy

Whole genome sequencing has opened the doors to Investigative genetic genealogy (IGG) analysis of challenging forensic samples that are not suitable for microarray genotyping. These samples still do not typically achieve high enough coverage for direct genotype calling, therefore a pipeline for imputation from low coverage sequencing data was evaluated using data from the 1000 Genomes Project. This pipeline generated results suitable for IGG down to 0.25X coverage. Additionally, forensic samples from a variety of tissue types and input amounts were sequenced and successfully uploaded to genetic genealogy databases after imputation.

Pedigree reconstruction for triploid apple cultivars using single nucleotide polymorphism array data

Societal Impact StatementMany economically, culturally, and historically important apple cultivars are triploids, which have three copies of each chromosome instead of the more typical two copies in diploids. Despite their prevalence and importance, there have been conflicting reports regarding their origin and their ability to beget diploids. New genetic analysis methodologies outlined in this study have clarified the genetic origin of triploid apple cultivars and suggest that triploidy has been a dead end in historic apple pedigrees. The specific results of this study have resolved the pedigrees of many cultivars, including the famous English cultivar Cox's Orange Pippin and the oldest known US cultivar Roxbury Russet.Summary In apple (Malus × domestica), most cultivars are diploid, though a sizeable number are triploids, which tend to be stronger growing, more robust, and bear larger fruit. However, triploidy is also associated with strongly reduced fertility. Some recorded pedigrees for historical apple cultivars include triploids as parents of diploids, despite this reputation of poor fertility. This information, coupled with some initiatives using triploids in breeding efforts, result in confusion about how possible or common it is for triploids to be parents of diploid offspring. To date, no studies have systematically evaluated and identified pedigrees of triploid apple cultivars to resolve these contradictions. Here, we describe a method to make triploid genotype calls using Illumina Infinium single nucleotide polymorphism (SNP) array data through a novel Python script: ploidyClassifier. SNP data for 219 unique triploids was compared alongside 2498 unique diploid apple accessions to conduct pedigree reconstruction. Unreduced gamete‐donating parents were identified for over half of the triploid accessions. From those, reduced gamete‐donating parents were identified for nearly half. Full or partial pedigrees for many classic triploids were uncovered, including that of the oldest known American cultivar, ‘Roxbury Russet’. All tested pedigrees from literature that listed triploids as parents of diploids were deemed false, including that of the well‐known ‘Cox's Orange Pippin’, whose previously unreported second parent was also identified here as ‘Rosemary Russet’. These results together suggest that historic triploids are mostly or solely the product of diploid parentage and that triploidy has been a dead end in historic apple pedigrees.

Development and application of arachnomelia syndrome genetic detection in four Chinese dual-purpose cattle populations

Arachnomelia syndrome (AS) is an autosomal recessive hereditary disorder in cattle, and affected calves are usually stillborn and characterized by complex anomalies. Therefore, identification of the carrier animals based on genetic tests is important for the control and elimination of this defect. The aim of this study was to build an effective workflow to routinely screen the AS mutations in bovine MOSC1 and SUOX genes and determine individuals carrying the AS mutations in four Chinese cattle populations.By combining the fluorescence-labeled PCR and capillary electrophoresis, we established a convenient and cost-effective workflow to detect two AS casual mutations simultaneously. Sanger sequencing was further used as a validation criterion and showed that 100% of the tests (37/37) had consistent results with genotype calls determined by our established workflow. Then, 582 bulls and 1-926 cows from Chinese dual-purpose cattle populations of Simmental, Sanhe, Shuxuan, and Xinjiang Brown were subjected to AS detection. The results showed that four bulls and 11 cows in the Simmental population, and six bulls and six cows in the Sanhe population were identified as AS carriers with the MOCS1 mutation c.1224_1225delCA. However, no animal was found to carry the c.363_364insG mutation in the SUOX gene. The frequencies of AS carriers were 1.08% and 1.65% in the Simmental and Sanhe populations, respectively, with a frequency of 1.076% in four populations. The pedigree analysis found that all carriers could be traced back to a common ancestor, the German Simmental sire ROMEL. Those findings suggested that this genetic defect spread into China mainly through the wide use of ROMEL. In conclusion, the occurrence of AS has not had a wide impact on the Chinese cattle industry; however, a screening system and mating strategy should be employed to gradually eliminate this recessive gene from the Chinese dual-purpose cattle population.

REViewer: haplotype-resolved visualization of read alignments in and around tandem repeats

BackgroundExpansions of short tandem repeats are the cause of many neurogenetic disorders including familial amyotrophic lateral sclerosis, Huntington disease, and many others. Multiple methods have been recently developed that can identify repeat expansions in whole genome or exome sequencing data. Despite the widely recognized need for visual assessment of variant calls in clinical settings, current computational tools lack the ability to produce such visualizations for repeat expansions. Expanded repeats are difficult to visualize because they correspond to large insertions relative to the reference genome and involve many misaligning and ambiguously aligning reads.ResultsWe implemented REViewer, a computational method for visualization of sequencing data in genomic regions containing long repeat expansions and FlipBook, a companion image viewer designed for manual curation of large collections of REViewer images. To generate a read pileup, REViewer reconstructs local haplotype sequences and distributes reads to these haplotypes in a way that is most consistent with the fragment lengths and evenness of read coverage. To create appropriate training materials for onboarding new users, we performed a concordance study involving 12 scientists involved in short tandem repeat research. We used the results of this study to create a user guide that describes the basic principles of using REViewer as well as a guide to the typical features of read pileups that correspond to low confidence repeat genotype calls. Additionally, we demonstrated that REViewer can be used to annotate clinically relevant repeat interruptions by comparing visual assessment results of 44 FMR1 repeat alleles with the results of triplet repeat primed PCR. For 38 of these alleles, the results of visual assessment were consistent with triplet repeat primed PCR.ConclusionsRead pileup plots generated by REViewer offer an intuitive way to visualize sequencing data in regions containing long repeat expansions. Laboratories can use REViewer and FlipBook to assess the quality of repeat genotype calls as well as to visually detect interruptions or other imperfections in the repeat sequence and the surrounding flanking regions. REViewer and FlipBook are available under open-source licenses at https://github.com/illumina/REViewer and https://github.com/broadinstitute/flipbook respectively.

Development of a Diagnostic Assay for Differentiation Between Genetic Groups in Clades I, II, III, and IV of Puccinia graminis f. sp. tritici.

Wheat stem rust has reemerged as a serious disease caused by new variants of Puccinia graminis f. sp. tritici. Variants with significant virulence and broad geographic distribution (Africa, Central Asia, and Europe) include the Ug99 race group, race TTRTF, and TKTTF race group. Genetic analysis has placed isolates representing these critical new virulent races into 12 genetic groups that make up clades I to IV. Development of molecular diagnostic assays for these 12 genetic groups will be an important component of global surveillance efforts. A single-nucleotide polymorphism database was mined for candidate markers that would differentiate between these 12 genetic groups. Thirty-five candidate markers were screened, and a core set of 17 markers was tested against a set of 94 isolates representing a broad range of genotypes and race phenotypes. These core markers were 100% accurate in identifying the 12 genetic groups for 52 isolates in clades I to IV, and no false positives were observed with nontarget isolates. The assay has built-in redundancy so that minor genetic changes or errors in genotyping calling will not affect the accuracy of the results. This assay is also effective in identifying the genetic groups in clade V from Germany and Georgia, the three main subgroups in North American clade VI, and clade VII consisting of race TTTTF found in North and South America. This assay provides a rapid diagnostic tool for both living and nonliving samples to detect these critical new races or race groups of P. graminis f. sp. tritici.[Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Analysis of genetic diversity and population structure among cultivated potato clones from Korea and global breeding programs

Characterizing the genetic diversity and population structure of breeding materials is essential for breeding to improve crop plants. The potato is an important non-cereal food crop worldwide, but breeding potatoes remains challenging owing to their auto-tetraploidy and highly heterozygous genome. We evaluated the genetic structure of a 110-line Korean potato germplasm using the SolCAP 8303 single nucleotide polymorphism (SNP) Infinium array and compared it with potato clones from other countries to understand the genetic landscape of cultivated potatoes. Following the tetraploid model, we conducted population structure analysis, revealing three subpopulations represented by two Korean potato groups and one separate foreign potato group within 110 lines. When analyzing 393 global potato clones, country/region-specific genetic patterns were revealed. The Korean potato clones exhibited higher heterozygosity than those from Japan, the United States, and other potato landraces. We also employed integrated extended haplotype homozygosity (iHS) and cross-population extended haplotype homozygosity (XP-EHH) to identify selection signatures spanning candidate genes associated with biotic and abiotic stress tolerance. Based on the informativeness of SNPs for dosage genotyping calls, 10 highly informative SNPs discriminating all 393 potatoes were identified. Our results could help understanding a potato breeding history that reflects regional adaptations and distinct market demands.

Abstract 1151: Pharmacogenomics genotyping from clinical somatic whole exome sequencing: Aldy, a computational tool

Abstract Background Pharmacogenomics (PGx) testing can reduce toxicities and improve efficacy of several drugs used to treat cancer and associated symptoms. PGx results can be determined from germline whole-exome sequencing (WES), but somatic mutations may cause discordance between tumor and germline DNA. Since clinical diagnostic sequencing in oncology frequently only includes tumor DNA, there would be clinical value in calling germline PGx genotypes from tumor DNA. Thus, the purpose of this study was to assess the feasibility of using somatic WES data to call germline PGx genotypes. Methods Germline and somatic WES data were obtained as part of the clinical workflow for 64 patients treated at the solid molecular tumor board clinic at Indiana University. Aldy v3.3 was implemented in LifeOmic’s Precision Health Cloud™ to call PGx genotypes from somatic WES. Somatic Aldy calls were compared with previously validated Aldy germline calls for 8 genes: CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, CYP4F2, DPYD, and TPMT. Somatic read depth was >100x, except for the intronic CYP3A4*22 variant, which was >30x. Results Somatic and germline Aldy calls were compared for a total of 512 genotypes and 56 (11%) calls were discordant. Discordant calls were most common for CYP2B6 (23.4%), followed by CYP2D6 (14.1%), CYP2C19 (10.9%), CYP2C8 (6.3%), and DPYD (6.3%). In contrast, all Aldy calls were concordant for CYP3A5 and TPMT. 38 out of 64 subjects (59%) had discordant calls for at least one gene. The most common first cancer diagnoses in our cohort were colorectal (9.3%), breast (7.8%), and pancreatic (7.8%), and the rates of discordant Aldy calls did not differ by cancer type (p>0.05 for all cancer types). Based on our analyses of discordant calls, we anticipate that adjusting Aldy’s thresholds for variant calling may allow Aldy to determine genotypes from somatic WES data. Conclusion In most cases, genotype calls of drug metabolism genes from tumor DNA reflected the germline genotypes; however, additional work needs to be done to determine if the remaining discordant calls can be corrected by modifying the informatics tools or if they are due to somatic mutations. Citation Format: Wilberforce A. Osei, Tyler Shugg, Reynold C. Ly, Steven M. Bray, Benjamin A. Salisbury, Ryan R. Ratcliff, Victoria M. Pratt, Ibrahim Numanagić, Todd Skaar. Pharmacogenomics genotyping from clinical somatic whole exome sequencing: Aldy, a computational tool [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1151.

Commonly used Hardy-Weinberg equilibrium filtering schemes impact population structure inferences using RADseq data.

Reduced representation sequencing (RRS) is a widely used method to assay the diversity of genetic loci across the genome of an organism. The dominant class of RRS approaches assay loci associated with restriction sites within the genome (restriction site associated DNA sequencing, or RADseq). RADseq is frequently applied to non‐model organisms since it enables population genetic studies without relying on well‐characterized reference genomes. However, RADseq requires the use of many bioinformatic filters to ensure the quality of genotyping calls. These filters can have direct impacts on population genetic inference, and therefore require careful consideration. One widely used filtering approach is the removal of loci that do not conform to expectations of Hardy–Weinberg equilibrium (HWE). Despite being widely used, we show that this filtering approach is rarely described in sufficient detail to enable replication. Furthermore, through analyses of in silico and empirical data sets we show that some of the most widely used HWE filtering approaches dramatically impact inference of population structure. In particular, the removal of loci exhibiting departures from HWE after pooling across samples significantly reduces the degree of inferred population structure within a data set (despite this approach being widely used). Based on these results, we provide recommendations for best practice regarding the implementation of HWE filtering for RADseq data sets.

DistAngsd: Fast and Accurate Inference of Genetic Distances for Next-Generation Sequencing Data.

Commonly used methods for inferring phylogenies were designed before the emergence of high-throughput sequencing and can generally not accommodate the challenges associated with noisy, diploid sequencing data. In many applications, diploid genomes are still treated as haploid through the use of ambiguity characters; while the uncertainty in genotype calling—arising as a consequence of the sequencing technology—is ignored. In order to address this problem, we describe two new probabilistic approaches for estimating genetic distances: distAngsd-geno and distAngsd-nuc, both implemented in a software suite named distAngsd. These methods are specifically designed for next-generation sequencing data, utilize the full information from the data, and take uncertainty in genotype calling into account. Through extensive simulations, we show that these new methods are markedly more accurate and have more stable statistical behaviors than other currently available methods for estimating genetic distances—even for very low depth data with high error rates.

Successful restoration of archived ovine formalin fixed paraffin-embedded tissue DNA and single nucleotide polymorphism analysis

Archived formalin fixed paraffin-embedded (FFPE) tissues are powerful tools in medicine, capable of harboring diagnostic and genetic answers to challenging clinical questions. Successful utilization of DNA derived from FFPE samples is dependent upon repairing DNA damage generated from the fixation process. Methods to repair FFPE DNA have been successful in human medicine for a variety of research and clinical applications, yet remain underutilized in veterinary medicine. Despite the available technology, our study is the first to evaluate the repair of FFPE derived DNA from veterinary species for single-nucleotide polymorphism (SNP) analysis using the Illumina OvineSNP50 BeadChip and Illumina FFPE QC and DNA Restore kit. To accomplish this, 48 ovine FFPE samples were run using the Illumina OvineSNP50 BeadChip with and without restoration. Compared to pre-restore data, we found increased sample call rates, SNP call frequency, and assay metrics for all samples post-restoration. Further, we utilized four sheep with available parallel fresh DNA and FFPE DNA to compare assay metrics and genotype calls between the two starting sample types. Although fresh samples generated increased call rates, we found 99% concordance in allele calls between restored FFPE and fresh DNA for all four samples. Our results indicate successful restoration and genotyping of ovine FFPE samples using this technology, with potential for utilization in other veterinary species.

0030 Development and Validation of a Metabolomic Risk Score for Obstructive Sleep Apnea across Race/Ethnicities

Abstract Introduction Obstructive sleep apnea (OSA) is a common disorder characterized by recurrent episodes of upper airway obstruction during sleep resulting in oxygen desaturation and sleep fragmentation, and associated with increased risk of adverse health outcomes. Metabolites are being increasingly used for biomarker discovery and evaluation of disease processes and progression. We aimed to develop a metabolomic risk score (MRS) for OSA and identify individual metabolites associated with OSA to provide insights into the pathogenesis of OSA. Methods We studied 219 metabolites and their associations the apnea hypopnea index (AHI) and with OSA, defined as AHI , in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) (n=3507) using two methods: (1) association analysis of individual metabolites, and (2) least absolute shrinkage and selection operator (LASSO) regression to identify a subset of metabolites that are jointly associated with OSA, and develop an MRS. We then validated the results in Multi-Ethnic Study of Atherosclerosis (MESA) (n=475), an independent dataset. Results HCHS/SOL participants were 41.72 years old on average, 50.7% female, and 10.2% had OSA. MESA individuals were 68.45 years old on average, 56.2% females, and 46.7% had OSA. When assessing the associations between OSA/AHI and individual metabolites, we identified seven metabolites significantly and positively associated with OSA in HCHS/SOL (FDR p<0.05), of which four associations - glutamate, oleoyl-linoleoyl-glycerol (18:1/18:2) (DAG(36:3)), linoleoyl-linoleoyl-glycerol (18:2/18:2) (DAG(36:4)) and phenylalanine, replicated in MESA (one sided-p value<0.05). The OSA-MRS, composed of 14 metabolites, was associated with 52% increase of risk for moderate to severe OSA (OR=1.52 [95% CI: 1.23-1.87] per 1 SD of OSA-MRS, p<.001) in the discovery dataset of HCHS/SOL and 44% increased risk (OR=1.44 [95% CI: 1.03-2.03] per 1 SD of OSA-MRS, p=0.034) in the validation dataset of MESA, both adjusted for demographic, lifestyle, and comorbidities. Similar albeit less significant associations were observed for AHI modeled continuously. Conclusion We developed an MRS that replicated in an independent multi-ethnic dataset, demonstrating the robustness of metabolomic-based OSA risk score to population heterogeneity. Replicated metabolite associations may provide insights into OSA-related molecular and metabolic mechanisms. Support (If Any) Support for metabolomics data was graciously provided by the JLH Foundation (Houston, Texas). The Hispanic Community Health Study/Study of Latinos was carried out as a collaborative study supported by contracts from the National Heart, Lung, and Blood Institute (NHLBI) to the University of North Carolina (N01-HC65233), University of Miami (N01-HC65234), Albert Einstein College of Medicine (N01-HC65235), Northwestern University (N01-HC65236), and San Diego State University (N01-HC65237). The following Institutes/Centers/Offices contribute to the HCHS/SOL through a transfer of funds to the NHLBI: National Center on Minority Health and Health Disparities, the National Institute of Deafness and Other Communications Disorders, the National Institute of Dental and Craniofacial Research, the National Institute of Diabetes and Digestive and Kidney Diseases, the National Institute of Neurological Disorders and Stroke, and the Office of Dietary Supplements. The authors thank the staff and participants of HCHS/SOL for their important contributions. MESA and the MESA SHARe project are conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with MESA investigators. Support for MESA is provided by contracts HHSN268201500003I, N01-HC-95159, N01-HC-95160, N01-HC-95161, N01-HC-95162, N01-HC-95163, N01-HC-95164, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169, UL1-TR-000040, UL1-TR-001079, UL1-TR-001420. MESA Family is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with MESA investigators. Support is provided by grants and contracts R01HL071051, R01HL071205, R01HL071250, R01HL071251, R01HL071258, R01HL071259, and by the National Center for Research Resources, Grant UL1RR033176. The provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences, CTSI grant UL1TR001881, and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center (DRC) grant DK063491 to the Southern California Diabetes Endocrinology Research Center. Molecular data for the Trans-Omics in Precision Medicine (TOPMed) program was supported by the National Heart, Lung and Blood Institute (NHLBI). ). Metabolomics for “NHLBI TOPMed: Multi-Ethnic Study of Atherosclerosis (MESA)” (phs001416) was performed at Broad Institute and Beth Israel Metabolomics Platform (HHSN268201600038I). Core support including centralized genomic read mapping and genotype calling, along with variant quality metrics and filtering were provided by the TOPMed Informatics Research Center (3R01HL-117626-02S1; contract HHSN268201800002I). Core support including phenotype harmonization, data management, sample-identity QC, and general program coordination were provided by the TOPMed Data Coordinating Center (R01HL-120393; U01HL-120393; contract HHSN268201800001I). We gratefully acknowledge the studies and participants who provided biological samples and data for TOPMed. This study was supported by NHLBI grant R35HL135818.

Evaluating the accuracy of variant calling methods using the frequency of parent-offspring genotype mismatch.

The use of next‐generation sequencing (NGS) data sets has increased dramatically over the last decade, but there have been few systematic analyses quantifying the accuracy of the commonly used variant caller programs. Here we used a familial design consisting of diploid tissue from a single lodgepole pine (Pinus contorta) parent and the maternally derived haploid tissue from 106 full‐sibling offspring, where mismatches could only arise due to mutation or bioinformatic error. Given the rarity of mutation, we used the rate of mismatches between parent and offspring genotype calls to infer the single nucleotide polymorphism (SNP) genotyping error rates of FreeBayes, HaplotypeCaller, SAMtools, UnifiedGenotyper, and VarScan. With baseline filtering HaplotypeCaller and UnifiedGenotyper yielded more SNPs and higher error rates by one to two orders of magnitude, whereas FreeBayes, SAMtools and VarScan yielded lower numbers of SNPs and more modest error rates. To facilitate comparison between variant callers we standardized each SNP set to the same number of SNPs using additional filtering, where UnifiedGenotyper consistently produced the smallest proportion of genotype errors, followed by HaplotypeCaller, VarScan, SAMtools, and FreeBayes. Additionally, we found that error rates were minimized for SNPs called by more than one variant caller. Finally, we evaluated the performance of various commonly used filtering metrics on SNP calling. Our analysis provides a quantitative assessment of the accuracy of five widely used variant calling programs and offers valuable insights into both the choice of variant caller program and the choice of filtering metrics, especially for researchers using non‐model study systems.