Genomic Balancing Act: deciphering DNA rearrangements in the complex chromosomal aberration involving 5p15.2, 2q31.1, and 18q21.32.

Despite extensive research into the genetic underpinnings of neurodevelopmental disorders (NDD), many clinical cases remain unresolved. We studied a female proband with a NDD, mildly dysmorphic facial features, and brain stem hypoplasia on neuroimaging. Comprehensive genomic analyses revealed a terminal 5p loss and a terminal 18q gain in the proband while a diploid copy number for chromosomes 5 and 18 in both parents. Genomic investigations in the proband identified an unbalanced translocation t(5;18) with additional genetic material from chromosome 2 (2q31.3) inserted at the breakpoint, pointing to a complex chromosomal rearrangement (CCR) involving 5p15.2, 2q31.3, and 18q21.32. Breakpoint junction analyses enabled by long-read genome sequencing unveiled the presence of four distinct junctions in the father, who is a carrier of a balanced CCR. The proband inherited from the father both the abnormal chromosome 5 resulting in segmental aneusomies of chr5 (loss) and chr18 (gain) and a der(2) homologue. Evidences suggest a chromoplexy mechanism for this CCR derivation, involving double-strand breaks (DSBs) repaired by non-homologous end joining (NHEJ) or alternative end joining (alt-EJ). The complexity of the CCR and the segregation of homologues elucidate the genetic model for this family. This study demonstrates the importance of combining multiple genomic technologies to uncover genetic causes of complex neurodevelopmental syndromes and to better understand genetic disease mechanisms.

INTRA- AND INTER-HOST EVOLUTION OF HUMAN NOROVIRUS IN HEALTHY ADULTS.

Background: Human noroviruses are a leading cause of acute and sporadic gastroenteritis worldwide. The evolution of human noroviruses in immunocompromised persons has been evaluated in many studies. Much less is known about the evolutionary dynamics of human norovirus in healthy adults. Methods: We used sequential samples collected from a controlled human infection study with GI.1/Norwalk/US/68 virus to evaluate intra- and inter-host evolution of a human norovirus in healthy adults. Up to 12 samples from day 1 to day 56 post-challenge were sequenced using a norovirus-specific capture probe method. Results: Complete genomes were assembled, even in samples that were below the limit of detection of standard RT-qPCR assays, up to 28 days post-challenge. Analysis of 123 complete genomes showed changes in the GI.1 genome in all persons, but there were no conserved changes across all persons. Single nucleotide variants resulting in non-synonymous amino acid changes were observed in all proteins, with the capsid VP1 and nonstructural protein NS3 having the largest numbers of changes. Conclusions: These data highlight the potential of a new capture-based sequencing approach to assemble human norovirus genomes with high sensitivity and demonstrate limited conserved immune pressure-driven evolution of GI.1 virus in healthy adults.

Examining intra-host genetic variation of RSV by short read high-throughput sequencing.

Every viral infection entails an evolving population of viral genomes. High-throughput sequencing technologies can be used to characterize such populations, but to date there are few published examples of such work. In addition, mixed sequencing data are sometimes used to infer properties of infecting genomes without discriminating between genome-derived reads and reads from the much more abundant, in the case of a typical active viral infection, transcripts. Here we apply capture probe-based short read high-throughput sequencing to nasal wash samples taken from a previously described group of adult hematopoietic cell transplant (HCT) recipients naturally infected with respiratory syncytial virus (RSV). We separately analyzed reads from genomes and transcripts for the levels and distribution of genetic variation by calculating per position Shannon entropies. Our analysis reveals a low level of genetic variation within the RSV infections analyzed here, but with interesting differences between genomes and transcripts in 1) average per sample Shannon entropies; 2) the genomic distribution of variation 'hotspots'; and 3) the genomic distribution of hotspots encoding alternative amino acids. In all, our results suggest the importance of separately analyzing reads from genomes and transcripts when interpreting high-throughput sequencing data for insight into intra-host viral genome replication, expression, and evolution.

Semi-supervised machine learning method for predicting homogeneous ancestry groups to assess Hardy-Weinberg equilibrium in diverse whole-genome sequencing studies.

Large-scale, multi-ethnic whole-genome sequencing (WGS) studies, such as the National Human Genome Research Institute Genome Sequencing Program's Centers for Common Disease Genomics (CCDG), play an important role in increasing diversity for genetic research. Before performing association analyses, assessing Hardy-Weinberg equilibrium (HWE) is a crucial step in quality control procedures to remove low quality variants and ensure valid downstream analyses. Diverse WGS studies contain ancestrally heterogeneous samples; however, commonly used HWE methods assume that the samples are homogeneous. Therefore, directly applying these to the whole dataset can yield statistically invalid results. To account for this heterogeneity, HWE can be tested on subsets of samples that have genetically homogeneous ancestries and the results aggregated at each variant. To facilitate valid HWE subset testing, we developed a semi-supervised learning approach that predicts homogeneous ancestries based on the genotype. This method provides a convenient tool for estimating HWE in the presence of population structure and missing self-reported race and ethnicities in diverse WGS studies. In addition, assessing HWE within the homogeneous ancestries provides reliable HWE estimates that will directly benefit downstream analyses, including association analyses in WGS studies. We applied our proposed method on the CCDG dataset, predicting homogeneous genetic ancestry groups for 60,545 multi-ethnic WGS samples to assess HWE within each group.

Frequency of pharmacogenomic variation and medication exposures among All of Us Participants.

Pharmacogenomics promises improved outcomes through individualized prescribing. However, the lack of diversity in studies impedes clinical translation and equitable application of precision medicine. We evaluated the frequencies of PGx variants, predicted phenotypes, and medication exposures using whole genome sequencing and EHR data from nearly 100k diverse All of Us Research Program participants. We report 100% of participants carried at least one pharmacogenomics variant and nearly all (99.13%) had a predicted phenotype with prescribing recommendations. Clinical impact was high with over 20% having both an actionable phenotype and a prior exposure to an impacted medication with pharmacogenomic prescribing guidance. Importantly, we also report hundreds of alleles and predicted phenotypes that deviate from known frequencies and/or were previously unreported, including within admixed American and African ancestry groups.

Inverted triplications formed by iterative template switches generate structural variant diversity at genomic disorder loci.

The duplication-triplication/inverted-duplication (DUP-TRP/INV-DUP) structure is a complex genomic rearrangement (CGR). Although it has been identified as an important pathogenic DNA mutation signature in genomic disorders and cancer genomes, its architecture remains unresolved. Here, we studied the genomic architecture of DUP-TRP/INV-DUP by investigating the DNA of 24 patients identified by array comparative genomic hybridization (aCGH) on whom we found evidence for the existence of 4 out of 4 predicted structural variant (SV) haplotypes. Using a combination of short-read genome sequencing (GS), long-read GS, optical genome mapping, and single-cell DNA template strand sequencing (strand-seq), the haplotype structure was resolved in 18 samples. The point of template switching in 4 samples was shown to be a segment of ∼2.2-5.5 kb of 100% nucleotide similarity within inverted repeat pairs. These data provide experimental evidence that inverted low-copy repeats act as recombinant substrates. This type of CGR can result in multiple conformers generating diverse SV haplotypes in susceptible dosage-sensitive loci.

Validation of Single-Nucleotide Mosaic Variants Through Droplet Digital PCR.

The detection, validation, and subsequent interpretation of potentially mosaic single-nucleotide variants (SNV) within next-generation sequencing data remains a challenge in both research and clinical laboratory settings. The ability to identify mosaic variants in high genome coverage sequencing data at levels of ≤1% underscores the necessity for developing guidelines and best practices to verify these variants orthogonally. Droplet digital PCR (ddPCR) has proven to be a powerful and precise method that allows for the determination of low-level variant fractions within a given sample. Herein we describe two precise ddPCR methods using either a fluorescent TaqMan hydrolysis probe approach or an EvaGreen fluorescent dye protocol. The TaqMan approach relies on two different fluorescent probes (FAM and HEX/VIC), each designed to amplify selectively only in the presence of a single nucleotide change denoting the variant or reference position. The fractional abundance is then calculated to determine the relative quantities of both alleles in the final sample. The EvaGreen protocol relies on two independent reactions with oligonucleotide primers designed with the single nucleotide change denoting the variant at the penultimate position of the primer. The relative amplification efficiency of both primer sets (reference and variant) can be compared to determine the mosaic level of a given variant. As the cost of high-coverage sequencing continues to decrease, the identification of potentially mosaic variants will also increase. The approaches outlined will allow clinicians and researchers a more precise determination of the true mosaic level of a given variant allowing them to better assess not only its potential pathogenicity but also its possible recurrence risk when offering genetic counseling to families. © 2024 Wiley Periodicals LLC. Basic Protocol: Droplet digital PCR (ddPCR) with TaqMan hydrolysis probes Alternate Protocol: EvaGreen oligonucleotide-specific ddPCR.

Whole genome sequencing based analysis of inflammation biomarkers in the Trans-Omics for Precision Medicine (TOPMed) consortium.

Inflammation biomarkers can provide valuable insight into the role of inflammatory processes in many diseases and conditions. Sequencing based analyses of such biomarkers can also serve as an exemplar of the genetic architecture of quantitative traits. To evaluate the biological insight, which can be provided by a multi-ancestry, whole-genome based association study, we performed a comprehensive analysis of 21 inflammation biomarkers from up to 38 465 individuals with whole-genome sequencing from the Trans-Omics for Precision Medicine (TOPMed) program (with varying sample size by trait, where the minimum sample size was n = 737 for MMP-1). We identified 22 distinct single-variant associations across 6 traits-E-selectin, intercellular adhesion molecule 1, interleukin-6, lipoprotein-associated phospholipase A2 activity and mass, and P-selectin-that remained significant after conditioning on previously identified associations for these inflammatory biomarkers. We further expanded upon known biomarker associations by pairing the single-variant analysis with a rare variant set-based analysis that further identified 19 significant rare variant set-based associations with 5 traits. These signals were distinct from both significant single variant association signals within TOPMed and genetic signals observed in prior studies, demonstrating the complementary value of performing both single and rare variant analyses when analyzing quantitative traits. We also confirm several previously reported signals from semi-quantitative proteomics platforms. Many of these signals demonstrate the extensive allelic heterogeneity and ancestry-differentiated variant-trait associations common for inflammation biomarkers, a characteristic we hypothesize will be increasingly observed with well-powered, large-scale analyses of complex traits.

Multilocus pathogenic variants contribute to intrafamilial clinical heterogeneity: a retrospective study of sibling pairs with neurodevelopmental disorders.

BACKGROUND: Multilocus pathogenic variants (MPVs) are genetic changes that affect multiple gene loci or regions of the genome, collectively leading to multiple molecular diagnoses. MPVs may also contribute to intrafamilial phenotypic variability between affected individuals within a nuclear family. In this study, we aim to gain further insights into the influence of MPVs on a disease manifestation in individual research subjects and explore the complexities of the human genome within a familial context. METHODS: We conducted a systematic reanalysis of exome sequencing data and runs of homozygosity (ROH) regions of 47 sibling pairs previously diagnosed with various neurodevelopmental disorders (NDD). RESULTS: We found siblings with MPVs driven by long ROH regions in 8.5% of families (4/47). The patients with MPVs exhibited significantly higher FROH values (p-value = 1.4e-2) and larger total ROH length (p-value = 1.8e-2). Long ROH regions mainly contribute to this pattern; the siblings with MPVs have a larger total size of long ROH regions than their siblings in all families (p-value = 6.9e-3). Whereas the short ROH regions in the siblings with MPVs are lower in total size compared to their sibling pairs with single locus pathogenic variants (p-value = 0.029), and there are no statistically significant differences in medium ROH regions between sibling pairs (p-value = 0.52). CONCLUSION: This study sheds light on the significance of considering MPVs in families with affected sibling pairs and the role of ROH as an adjuvant tool in explaining clinical variability within families. Identifying individuals carrying MPVs may have implications for disease management, identification of possible disease risks to different family members, genetic counseling and exploring personalized treatment approaches.

NODAL variants are associated with a continuum of laterality defects from simple D-transposition of the great arteries to heterotaxy.

BACKGROUND: NODAL signaling plays a critical role in embryonic patterning and heart development in vertebrates. Genetic variants resulting in perturbations of the TGF-ß/NODAL signaling pathway have reproducibly been shown to cause laterality defects in humans. To further explore this association and improve genetic diagnosis, the study aims to identify and characterize a broader range of NODAL variants in a large number of individuals with laterality defects. METHODS: We re-analyzed a cohort of 321 proband-only exomes of individuals with clinically diagnosed laterality congenital heart disease (CHD) using family-based, rare variant genomic analyses. To this cohort we added 12 affected subjects with known NODAL variants and CHD from institutional research and clinical cohorts to investigate an allelic series. For those with candidate contributory variants, variant allele confirmation and segregation analysis were studied by Sanger sequencing in available family members. Array comparative genomic hybridization and droplet digital PCR were utilized for copy number variants (CNV) validation and characterization. We performed Human Phenotype Ontology (HPO)-based quantitative phenotypic analyses to dissect allele-specific phenotypic differences. RESULTS: Missense, nonsense, splice site, indels, and/or structural variants of NODAL were identified as potential causes of heterotaxy and other laterality defects in 33 CHD cases. We describe a recurrent complex indel variant for which the nucleic acid secondary structure predictions implicate secondary structure mutagenesis as a possible mechanism for formation. We identified two CNV deletion alleles spanning NODAL in two unrelated CHD cases. Furthermore, 17 CHD individuals were found (16/17 with known Hispanic ancestry) to have the c.778G > A:p.G260R NODAL missense variant which we propose reclassification from variant of uncertain significance (VUS) to likely pathogenic. Quantitative HPO-based analyses of the observed clinical phenotype for all cases with p.G260R variation, including heterozygous, homozygous, and compound heterozygous cases, reveal clustering of individuals with biallelic variation. This finding provides evidence for a genotypic-phenotypic correlation and an allele-specific gene dosage model. CONCLUSION: Our data further support a role for rare deleterious variants in NODAL as a cause for sporadic human laterality defects, expand the repertoire of observed anatomical complexity of potential cardiovascular anomalies, and implicate an allele specific gene dosage model.

Somatic mutations of esophageal adenocarcinoma: a comparison between Black and White patients.

Esophageal adenocarcinoma is the most common histological subtype of esophageal cancer in Western countries and shows poor prognosis with rapid growth. EAC is characterized by a strong male predominance and racial disparity. EAC is up to fivefold more common among Whites than Blacks, yet Black patients with EAC have poorer survival rates. The racial disparity remains largely unknown, and there is limited knowledge of mutations in EAC regarding racial disparities. We used whole-exome sequencing to show somatic mutation profiles derived from tumor samples from 18 EAC male patients. We identified three molecular subgroups based on the pre-defined esophageal cancer-specific mutational signatures. Group 1 is associated with age and NTHL1 deficiency-related signatures. Group 2 occurs primarily in Black patients and is associated with signatures related to DNA damage from oxidative stress and NTHL1 deficiency-related signatures. Group 3 is associated with defective homologous recombination-based DNA often caused by BRCA mutation in White patients. We observed significantly mutated race related genes (LCE2B in Black, SDR39U1 in White) were (q-value < 0.1). Our findings underscore the possibility of distinct molecular mutation patterns in EAC among different races. Further studies are needed to validate our findings, which could contribute to precision medicine in EAC.

Closing the gap: Solving complex medically relevant genes at scale.

Comprehending the mechanism behind human diseases with an established heritable component represents the forefront of personalized medicine. Nevertheless, numerous medically important genes are inaccurately represented in short-read sequencing data analysis due to their complexity and repetitiveness or the so-called 'dark regions' of the human genome. The advent of PacBio as a long-read platform has provided new insights, yet HiFi whole-genome sequencing (WGS) cost remains frequently prohibitive. We introduce a targeted sequencing and analysis framework, Twist Alliance Dark Genes Panel (TADGP), designed to offer phased variants across 389 medically important yet complex autosomal genes. We highlight TADGP accuracy across eleven control samples and compare it to WGS. This demonstrates that TADGP achieves variant calling accuracy comparable to HiFi-WGS data, but at a fraction of the cost. Thus, enabling scalability and broad applicability for studying rare diseases or complementing previously sequenced samples to gain insights into these complex genes. TADGP revealed several candidate variants across all cases and provided insight into LPA diversity when tested on samples from rare disease and cardiovascular disease cohorts. In both cohorts, we identified novel variants affecting individual disease-associated genes (e.g., IKZF1, KCNE1). Nevertheless, the annotation of the variants across these 389 medically important genes remains challenging due to their underrepresentation in ClinVar and gnomAD. Consequently, we also offer an annotation resource to enhance the evaluation and prioritization of these variants. Overall, we can demonstrate that TADGP offers a cost-efficient and scalable approach to routinely assess the dark regions of the human genome with clinical relevance.

Defining and Reducing Variant Classification Disparities.

Background: Multiplexed Assays of Variant Effects (MAVEs) can test all possible single variants in a gene of interest. The resulting saturation-style data may help resolve variant classification disparities between populations, especially for variants of uncertain significance (VUS). Methods: We analyzed clinical significance classifications in 213,663 individuals of European-like genetic ancestry versus 206,975 individuals of non-European-like genetic ancestry from All of Us and the Genome Aggregation Database. Then, we incorporated clinically calibrated MAVE data into the Clinical Genome Resource's Variant Curation Expert Panel rules to automate VUS reclassification for BRCA1, TP53, and PTEN . Results: Using two orthogonal statistical approaches, we show a higher prevalence ( p ≤5.95e-06) of VUS in individuals of non-European-like genetic ancestry across all medical specialties assessed in all three databases. Further, in the non-European-like genetic ancestry group, higher rates of Benign or Likely Benign and variants with no clinical designation ( p ≤2.5e-05) were found across many medical specialties, whereas Pathogenic or Likely Pathogenic assignments were higher in individuals of European-like genetic ancestry ( p ≤2.5e-05). Using MAVE data, we reclassified VUS in individuals of non-European-like genetic ancestry at a significantly higher rate in comparison to reclassified VUS from European-like genetic ancestry ( p =9.1e-03) effectively compensating for the VUS disparity. Further, essential code analysis showed equitable impact of MAVE evidence codes but inequitable impact of allele frequency ( p =7.47e-06) and computational predictor ( p =6.92e-05) evidence codes for individuals of non-European-like genetic ancestry. Conclusions: Generation of saturation-style MAVE data should be a priority to reduce VUS disparities and produce equitable training data for future computational predictors.

Genomic Balancing Act: Deciphering DNA rearrangements in the Complex Chromosomal Aberration involving 5p15.2, 2q31.1 and 18q21.32.

Despite extensive research into the genetic underpinnings of neurodevelopmental disorders (NDD), many clinical cases remain unresolved. We studied a female proband with a NDD, mildly dysmorphic facial features, and brain stem hypoplasia on neuroimaging. Comprehensive genomic analyses revealed a terminal 5p loss and terminal 18q gain in the proband while a diploid copy number for chromosomes 5 and 18 in both parents. Genomic investigations in the proband identified an unbalanced translocation t(5;18) with additional genetic material from chromosome 2 (2q31.3) inserted at the breakpoint, pointing to a complex chromosomal rearrangement (CCR) involving 5p15.2, 2q31.3, and 18q21.32. Breakpoint junction analyses enabled by long read genome sequencing unveiled the presence of four distinct junctions in the father, who is carrier of a balanced CCR. The proband inherited from the father both the abnormal chromosome 5 resulting in segmental aneusomies of chr5 (loss) and chr18 (gain) and a der(2) homologue. Evidences suggest a chromoplexy mechanism for this CCR derivation, involving double-strand breaks (DSBs) repaired by non-homologous end joining (NHEJ) or alternative end joining (alt-EJ). The complexity of the CCR and the segregation of homologues elucidate the genetic model for this family. This study demonstrates the importance of combining multiple genomic technologies to uncover genetic causes of complex neurodevelopmental syndrome and to better understand genetic disease mechanisms.

Empowering personalized pharmacogenomics with generative AI solutions.

OBJECTIVE: This study evaluates an AI assistant developed using OpenAI's GPT-4 for interpreting pharmacogenomic (PGx) testing results, aiming to improve decision-making and knowledge sharing in clinical genetics and to enhance patient care with equitable access. MATERIALS AND METHODS: The AI assistant employs retrieval-augmented generation (RAG), which combines retrieval and generative techniques, by harnessing a knowledge base (KB) that comprises data from the Clinical Pharmacogenetics Implementation Consortium (CPIC). It uses context-aware GPT-4 to generate tailored responses to user queries from this KB, further refined through prompt engineering and guardrails. RESULTS: Evaluated against a specialized PGx question catalog, the AI assistant showed high efficacy in addressing user queries. Compared with OpenAI's ChatGPT 3.5, it demonstrated better performance, especially in provider-specific queries requiring specialized data and citations. Key areas for improvement include enhancing accuracy, relevancy, and representative language in responses. DISCUSSION: The integration of context-aware GPT-4 with RAG significantly enhanced the AI assistant's utility. RAG's ability to incorporate domain-specific CPIC data, including recent literature, proved beneficial. Challenges persist, such as the need for specialized genetic/PGx models to improve accuracy and relevancy and addressing ethical, regulatory, and safety concerns. CONCLUSION: This study underscores generative AI's potential for transforming healthcare provider support and patient accessibility to complex pharmacogenomic information. While careful implementation of large language models like GPT-4 is necessary, it is clear that they can substantially improve understanding of pharmacogenomic data. With further development, these tools could augment healthcare expertise, provider productivity, and the delivery of equitable, patient-centered healthcare services.

Germline Genetic Testing and Survival Outcomes Among Children With Rhabdomyosarcoma: A Report From the Children's Oncology Group.

Importance: Determining the impact of germline cancer-predisposition variants (CPVs) on outcomes could inform novel approaches to testing and treating children with rhabdomyosarcoma. Objective: To assess whether CPVs are associated with outcome among children with rhabdomyosarcoma. Design, Setting, and Participants: In this cohort study, data were obtained for individuals, aged 0.01-23.23 years, newly diagnosed with rhabdomyosarcoma who were treated across 171 Children's Oncology Group sites from March 15, 1999, to December 8, 2017. Data analysis was performed from June 16, 2021, to May 15, 2023. Exposure: The presence of a CPV in 24 rhabdomyosarcoma-associated cancer-predisposition genes (CPGs) or an expanded set of 63 autosomal-dominant CPGs. Main Outcomes and Measures: Overall survival (OS) and event-free survival (EFS) were the main outcomes, using the Kaplan-Meier estimator to assess survival probabilities and the Cox proportional hazards regression model to adjust for clinical covariates. Analyses were stratified by tumor histology and the fusion status of PAX3 or PAX7 to the FOXO1 gene. Results: In this study of 580 individuals with rhabdomyosarcoma, the median patient age was 5.9 years (range, 0.01-23.23 years), and the male-to-female ratio was 1.5 to 1 (351 [60.5%] male). For patients with CPVs in rhabdomyosarcoma-associated CPGs, EFS was 48.4% compared with 57.8% for patients without a CPV (P = .10), and OS was 53.7% compared with 65.3% for patients without a CPV (P = .06). After adjustment, patients with CPVs had significantly worse OS (adjusted hazard ratio [AHR], 2.49 [95% CI, 1.39-4.45]; P = .002), and the outcomes were not better among patients with embryonal histology (EFS: AHR, 2.25 [95% CI, 1.25-4.06]; P = .007]; OS: AHR, 2.83 [95% CI, 1.47-5.43]; P = .002]). These associations were not due to the development of a second malignant neoplasm, and importantly, patients with fusion-negative rhabdomyosarcoma who harbored a CPV had similarly inferior outcomes as patients with fusion-positive rhabdomyosarcoma without CPVs (EFS: AHR, 1.35 [95% CI, 0.71-2.59]; P = .37; OS: AHR, 1.71 [95% CI, 0.84-3.47]; P = .14). There were no significant differences in outcome by CPV status of the 63 CPG set. Conclusions and Relevance: This cohort study identified a group of patients with embryonal rhabdomyosarcoma who had a particularly poor outcome. Other important clinical findings included that individuals with TP53 had poor outcomes independent of second malignant neoplasms and that patients with fusion-negative rhabdomyosarcoma who harbored a CPV had outcomes comparable to patients with fusion-positive rhabdomyosarcoma. These findings suggest that germline CPV testing may aid in clinical prognosis and should be considered in prospective risk-based clinical trials.

Genetic sex validation for sample tracking in next-generation sequencing clinical testing.

OBJECTIVE: Data from DNA genotyping via a 96-SNP panel in a study of 25,015 clinical samples were utilized for quality control and tracking of sample identity in a clinical sequencing network. The study aimed to demonstrate the value of both the precise SNP tracking and the utility of the panel for predicting the sex-by-genotype of the participants, to identify possible sample mix-ups. RESULTS: Precise SNP tracking showed no sample swap errors within the clinical testing laboratories. In contrast, when comparing predicted sex-by-genotype to the provided sex on the test requisition, we identified 110 inconsistencies from 25,015 clinical samples (0.44%), that had occurred during sample collection or accessioning. The genetic sex predictions were confirmed using additional SNP sites in the sequencing data or high-density genotyping arrays. It was determined that discrepancies resulted from clerical errors (49.09%), samples from transgender participants (3.64%) and stem cell or bone marrow transplant patients (7.27%) along with undetermined sample mix-ups (40%) for which sample swaps occurred prior to arrival at genome centers, however the exact cause of the events at the sampling sites resulting in the mix-ups were not able to be determined.