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[Preprint]. 2023 Sep 11:rs.3.rs-3304685.
doi: 10.21203/rs.3.rs-3304685/v1.

Genetic Sex Validation for Sample Tracking in Clinical Testing

Jianhong Hu  1 , Viktoriya Korchina  1 , Hana Zouk  2 , Maegan V Harden  3 , David Murdock  1 , Alyssa Macbeth  3 , Steven M Harrison  2 , Niall Lennon  3 , Christie Kovar  1 , Adithya Balasubramanian  1 , Lan Zhang  1 , Gauthami Chandanavelli  1 , Divya Pasham  1 , Robb Rowley  4 , Ken Wiley  4 , Maureen E Smith  5 , Adam Gordon  5 , Gail P Jarvik  6 , Patrick Sleiman  7 , Melissa A Kelly  8 , Harris T Bland  9 , Mullai Murugan  1 , Eric Venner  1 , Eric Boerwinkle  1 , Cynthia Prows  10 , Lisa Mahanta  2 , Heidi L Rehm  3 , Richard A Gibbs  1 , Donna M Muzny  1
Affiliations

Genetic Sex Validation for Sample Tracking in Clinical Testing

Jianhong Hu et al. Res Sq. .

Update in

  • Genetic sex validation for sample tracking in next-generation sequencing clinical testing.
    Hu J, Korchina V, Zouk H, Harden MV, Murdock D, Macbeth A, Harrison SM, Lennon N, Kovar C, Balasubramanian A, Zhang L, Chandanavelli G, Pasham D, Rowley R, Wiley K, Smith ME, Gordon A, Jarvik GP, Sleiman P, Kelly MA, Bland HT, Murugan M, Venner E, Boerwinkle E; eMERGE III consortium; Prows C, Mahanta L, Rehm HL, Gibbs RA, Muzny DM. Hu J, et al. BMC Res Notes. 2024 Mar 3;17(1):62. doi: 10.1186/s13104-024-06723-w. BMC Res Notes. 2024. PMID: 38433186 Free PMC article.

Abstract

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, samples from transgender participants and stem cell or bone marrow transplant patients along with undetermined sample mix-ups.

Keywords: Clinical testing; Next Generation Sequencing (NGS); SNP genotyping; Sex concordance.

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Conflict of interest statement

Competing interests JH, DM, MM, RAG, DMM disclose that the Baylor Genetics Laboratory is co-owned by Baylor College of Medicine. EV is cofounder of Codified Genomics, which provides variant interpretation services. DM has received consulting fees from Illumina. The remaining authors disclose they have no competing interests.

Figures

Figure 1
Figure 1. eMERGE sample processing workflow
Steps indicating where aliquots of DNA are taken from samples that are presented to the Clinical DNA Sequencing Laboratory for accession, to test via the Fluidigm 96-SNP panel assay. Data from the Fluidigm 96-SNP panel assay are compared with DNA sequence data from the DNA sequencing pipeline as a quality control step, ahead of the Automated Clinical Reporting step.
Figure 2
Figure 2. Scatter Plot Analysis of 96-SNP Panel Reveals Sample Contamination
Scatter plot analysis from vendor software, showing a normal DNA male sample (A) or a contaminated sample containing a mixture of male and female DNAs (B). Panel 1–3: SNPs on X Chromosome; Panel 4–6: SNPs on Y Chromosome; Panel 7–9: autosomal SNPs. Each panel shows the data from a single SNP, as compared to clusters from all other SNPs. Clusters are shown as either homozygous (red or green), or heterozygous (blue) positions. In Panels B2, 3, 7–9, single SNPS are represented as outside the expected (arrows) resulting in erroneous or ‘no-call’ from the software.
See this image and copyright information in PMC

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