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. 2022 Nov;10(8):1605-1624.
doi: 10.1111/andr.13269. Epub 2022 Sep 7.

Whole-genome sequencing identifies new candidate genes for nonobstructive azoospermia

Affiliations

Whole-genome sequencing identifies new candidate genes for nonobstructive azoospermia

Agnieszka Malcher et al. Andrology. 2022 Nov.

Abstract

Background: Genetic causes that lead to spermatogenetic failure in patients with nonobstructive azoospermia (NOA) have not been yet completely established.

Objective: To identify low-frequency NOA-associated single nucleotide variants (SNVs) using whole-genome sequencing (WGS).

Materials and methods: Men with various types of NOA (n = 39), including samples that had been previously tested with whole-exome sequencing (WES; n = 6) and did not result in diagnostic conclusions. Variants were annotated using the Ensembl Variant Effect Predictor, utilizing frequencies from GnomAD and other databases to provide clinically relevant information (ClinVar), conservation scores (phyloP), and effect predictions (i.e., MutationTaster). Structural protein modeling was also performed.

Results: Using WGS, we revealed potential NOA-associated SNVs, such as: TKTL1, IGSF1, ZFPM2, VCX3A (novel disease causing variants), ESX1, TEX13A, TEX14, DNAH1, FANCM, QRICH2, FSIP2, USP9Y, PMFBP1, MEI1, PIWIL1, WDR66, ZFX, KCND1, KIAA1210, DHRSX, ZMYM3, FAM47C, FANCB, FAM50B (genes previously known to be associated with infertility) and ALG13, BEND2, BRWD3, DDX53, TAF4, FAM47B, FAM9B, FAM9C, MAGEB6, MAP3K15, RBMXL3, SSX3 and FMR1NB genes, which may be involved in spermatogenesis.

Discussion and conclusion: In this study, we identified novel potential candidate NOA-associated genes in 29 individuals out of 39 azoospermic males. Note that in 5 out of 6 patients subjected previously to WES analysis, which did not disclose potentially causative variants, the WGS analysis was successful with NOA-associated gene findings.

Keywords: biomarkers; infertility; nonobstructive azoospermia; spermatogenesis; whole-genome sequencing.

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Conflict of interest statement

The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.

Figures

FIGURE 1
FIGURE 1
Structural modeling of TKTL1, IGSF1, ZFPM2, and VCX3A reveals potential mechanisms related to disease. (A) Diagram of TKTL1 with the indicated domains., Numbers below represent amino acid positions in the primary structure. Above, positions of mutations of interest are shown. *Location of premature truncation due to the frameshift associated with D90M. Below this scheme, the model of the homodimer of TKTL1 in the schematic representation is shown. One monomer is colored blue, and the other is colored white. Green spheres represent positions of chelation of the calcium ion cofactor. Red boxes show the position of E534 in the context of the putative homodimer. The inset shows the position of E534 and the putative hydrogen bonds of its side chain carboxyl group with the backbone of amides of residues 542 and 543. (B) Phyre2‐33‐based structural homology modeling of IGSF1. The predicted orientation of IGSF1 relative to the plasma membrane is indicated with modeled tandem immunoglobulin‐like C2‐set motifs shown in cartoon view and numbered., Locations of residues of interest are indicated. Disulfide bonds are shown as sticks, and unmodeled loops are shown as dotted black lines. Insets show the environment around labeled residues. The most energetically favorable rotamers of L395R are also shown. Red arrows indicate putative clashes between the mutant arginine residue and surrounding amino acids. (C) Linear organization of ZFPM2. ZnF, zinc finger; PR‐SET, PR‐SET domain. Below, residues of interest are indicated along the linear diagram. (D) Linear organization of VCX3A. The eight L–S–Q–E–S–[E or Q]–V–E–E–P sequence motifs are shown as light gray boxes

References

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Publication types

Supplementary concepts