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Article

Clinical Evaluation of a Custom Gene Panel as a Tool for Precision Male Infertility Diagnosis by Next-Generation Sequencing

by
Rossella Cannarella
1,
Vincenza Precone
2,
Giulia Guerri
3,
Gian Maria Busetto
4,
Gian Carlo Di Renzo
5,
Sandro Gerli
5,
Elena Manara
2,
Astrit Dautaj
6,*,
Matteo Bertelli
2,3,6 and
Aldo Eugenio Calogero
1
1
Department of Clinical and Experimental Medicine, University of Catania, 95124 Catania, Italy
2
MAGI EUREGIO, 39100 Bolzano, Italy
3
MAGI’S LAB, 38068 Rovereto, Italy
4
Department of Urology, “Sapienza” University of Rome, Policlinico Umberto I, 00185 Rome, Italy
5
Department of Surgical and Biomedical Sciences, University of Perugia, 06123 Perugia, Italy
6
EBTNA-LAB, Via delle Maioliche, 57/G, 38068 Rovereto, Italy
*
Author to whom correspondence should be addressed.
Life 2020, 10(10), 242; https://doi.org/10.3390/life10100242
Submission received: 21 September 2020 / Revised: 9 October 2020 / Accepted: 12 October 2020 / Published: 15 October 2020
(This article belongs to the Special Issue The Increasing Role of Next Generation Sequencing Methods in Mutation Analysis)
Versions Notes

Abstract

:
Background: Up to 15% of couples are infertile and male factor infertility accounts for approximately 50% of these cases. Male infertility is a multifactorial pathological condition. The genetic of male infertility is very complex and at least 2000 genes are involved in its etiology. Genetic testing by next-generation sequencing (NGS) technologies can be relevant for its diagnostic value in male infertile patients. Therefore, the aim of this study was to implement the diagnostic offer with the use of an NGS panel for the identification of genetic variants. Methods: We developed an NGS gene panel that we used in 22 male infertile patients. The panel consisted of 110 genes exploring the genetic causes of male infertility; namely spermatogenesis failure due to single-gene mutations, central hypogonadism, androgen insensitivity syndrome, congenital hypopituitarism, and primary ciliary dyskinesia. Results: NGS and a subsequent sequencing of the positive pathogenic or likely pathogenic variants, 5 patients (23%) were found to have a molecular defect. In particular, pathogenic variants were identified in TEX11, CCDC39, CHD7, and NR5A1 genes. Moreover, 14 variants of unknown significance and 7 novel variants were found that require further functional studies and family segregation. Conclusion: This extended NGS-based diagnostic approach may represent a useful tool for the diagnosis of male infertility. The development of a custom-made gene panel by NGS seems capable of reducing the proportion of male idiopathic infertility.

1. Introduction

It is estimated that about 48.5 million couples worldwide are affected by infertility [1,2,3]. Epidemiological data have addressed to the male factor an etiologic role, alone or in combination, in the half of cases of couple’s infertility [4]. Genetic causes of male infertility, as well as the effects of their transmission to the offspring are still not fully understood [5]. The primary male infertility can be associated with abnormal semen or normal semen (idiopathic infertility). Instead, the secondary male infertility is due to systemic or syndromic genetic defects [6]. Disorders of sex development, ambiguous genitalia and androgen insensitivity, central hypogonadism, congenital hypopituitarism, and primary ciliary dyskinesia (PCD) can occur in syndromic forms [6,7,8,9,10,11]. Laboratory tests are of pivotal importance for a correct etiological classification of male infertility and for the choice of an effective treatment [12,13]. In addition to traditional first level diagnostic tests (seminal fluid analysis, hormone measurement, bacteriological analysis, and the search for anti-sperm antibodies), second level diagnostic tests such as sperm function tests and genetic analysis are useful for the assessment of male infertility [13]. In particular, genetic analysis is of relevance since about 15–30% of male infertility cases may recognize a genetic factor [14,15,16]. Genetic disorders related to male infertility include monogenic diseases and whole or partial chromosomal aberrations. Over 200 genetic conditions related to male infertility are reported in Online Mendelian Inheritance in Man (OMIM) database [17,18]. The identification of the genetic defect in the management of infertility allows also to establish the risk of its possible inheritance in preconception screening and the optimization of assisted fertilization techniques [19,20,21]. The genetic tests commonly used for male infertility diagnosis include karyotyping to detect numerical or structural abnormalities and PCR (polymerase chain reaction) to detect known genetic anomalies. However, it must be considered that the etiology remains elusive in about 40% of cases of male infertility (idiopathic forms) that, very likely, have a genetic unknown background [22,23]. Moreover, also it would be necessary to consider the role of recently discovered autosomal single-gene disorders in male infertility [24]. In fact, long been known chromosomal syndromes associated with infertility diagnosed by karyotype analysis, but only in recent years studies have been conducted on specific chromosomal regions and identified single genes linked to infertility problems. About 30% of infertility cases are still apparently sine causa and it is difficult for these to be syndromic conditions, but rather for conditions in which the reproductive defect is the only diagnostic indication [25,26]. Knowledge of the molecular defect attributable to single genes could lead to the development of targeted therapies to correct the genetic defect. The complexity of genetic tests for the diagnosis of infertility is continuously and rapidly growing thanks above all to the advent of new biomolecular and bioinformatics technologies. Within this scenario, the next-generation sequencing (NGS) technique can improve and personalize male infertility diagnosis. In addition, NGS can allow the simultaneous analysis of a large cohorts of infertile patients and the screening of multiple disease-causing variants of many genes [27]. The use of multigene panels can be a useful tool to improve the diagnostic framework of the patients [21,27]. Therefore, the aim of this study was to implement the diagnostic offer with the use of an NGS panel for the identification of genetic variants that may support a more accurate management of male infertility.

2. Results

Twenty-two male patients with infertility were analyzed with a NGS customized panel. Their median age was 37 years (range 19–56). The diagnostic suspects, made matching data coming from anamnesis, physical examination, hormone values, scrotal ultrasound, and/or sperm analysis, were primary spermatogenic defects (n = 16), central hypogonadism (n = 3), androgen insensitivity (n = 1), congenital hypopituitarism (n = 1), and primary ciliary dyskinesia (n = 1). For each patient, only the genes of the panel related to the diagnostic suspect were analyzed because the analysis was for diagnostic purposes. Genetic variants identified in the analyzed population by NGS are reported in Supplementary Table S1, whereas variants identified in the patients with a positive genetic diagnosis are reported in Table 1.
In clinical utility assessment, 5 patients (23%) resulted positive for the diagnostic test.

2.1. Case 1

Case 1 was a 41-year-old patient, trying to reach fatherhood in the last 2 years. The female partner was 32 years old and no female factor infertility was found. Patient’s physical examination was unremarkable, showing normal androgenization and no signs of genital malformation. Sperm analysis (which was performed according to the WHO 2010 criteria) showed oligoasthenozoospermia for three times. The mean (range) conventional sperm parameters were: 1.7 (0.36–4) million/mL for sperm concentration, 6.6 (2.5–14) million/ejaculate for total sperm count, 7 (3–10%) for sperm progressive motility, 35.3 (20–56) for total sperm motility, 5.7 (3–10%) for spermatozoa with normal form. Seminal fluid leukocytes were <1 million/mL in all specimens. Follicle-stimulating hormone (FSH) serum values were 8.1 IU/L. At scrotal ultrasound, testicular volumes were 14.7 mL and 14.1 mL for the right and the left testis, respectively. Male accessory gland infection, varicocele, or other acquired causes of male infertility were carefully assessed and could be excluded.
The patient was hence suspected of a defect of primary spermatogenic failure due to mutation in single genes. The analyzed sample showed the presence of two sequence alterations in the TEX11 gene located in the chromosome X, namely the pathogenic variant p.(Val763Ala) (c.2288T > C) (rs200139216) [28] and the likely benign variant p.(Thr259Ile) (c.776C > T) (rs762957753). In addition, it has also been identified in ZPBP (Zona Pellucida Binding Protein) gene the likely benign variant p.(Arg17Pro) (c.50G > C) (rs202231065) in heterozygosity. ZPBP gene ex:1 (chr7:50093185-50093209) was re-sequenced by Sanger (NGS coverage: 4,5X).

2.2. Case 2

Case 2 was a 19-year-old male patient suspected of having a primary ciliary dyskinesia. Physical examination showed normal androgenization, no genital malformation, normal penile size, and testicular volume, but the presence of right varicocele. At instrumental examination, he had dextrocardia and bronchiectasia. The patient was healthy and did not have respiratory symptoms. Sperm analysis documented azoospermia. After scleroembolization, he had oligoasthenoteratozoospermia. Transmission electronic microscopy analysis documented abnormal connecting piece and the absence of outer dynein arms in the sperm axoneme. It the respiratory cilia it showed abnormal number and position of peripheral microtubules and of central pair. The analyzed sample showed the presence of three sequence alterations in CCDC39 (Coiled-Coil Domain Containing 39) gene, namely the pathogenic variant c.610-2A > G (rs756235547) [29], a variant with uncertain pathogenic significance p.(Arg811Cys) (c.2431C > T) (rs574993914) and a variant probably benign p.(Thr182Ser) (c.545C > G) (rs112738198), all in heterozygosity. Moreover, it has also been identified in CDC151 gene a variant with uncertain pathogenic significance p.(Thr205Ile) (c.614C > T) (rs35061520) in heterozygosity detected by Sanger sequencing. However, since this gene is associated with a recessive inheritance, it is unlikely that this mutation alone could cause PCD.

2.3. Case 3

Case 3 was a 26-year-old male patient with reversal central hypogonadism. At the age of 14 years old, due to the absence of puberty, he underwent to genetic testing and pituitary imaging, revealing abnormally low gonadotropins (the pituitary function was normal for the other pituitary hormones) and the absence of abnormalities at imaging. He was then prescribed gonadotropins. At the age of 22 years, the patient reached a complete degree of androgenization. Withdrawal from treatment revealed the persistence of low gonadotropins and the diagnosis of central hypogonadism was confirmed. No abnormality of smell sense was referred by the patient. He was then prescribed testosterone replacement therapy (TRT). At the age of 24 years, TRT was discontinued. At hormone testing, gonadotropins were found within the normal range. At scrotal ultrasound, testicular volumes were 5.8 mL and 5 mL, in the right and in the left testis, respectively. At the sperm analysis, a severe oligoasthenoteratozoospermia was found after 5 months from TRT withdrawal. Specifically, 5 spermatozoa in the whole specimen were found. None of them were motile and normally shaped. A severe left varicocele was found, and the patient was then counseled for scleroembolization.
At genetic testing, pathogenic variant p.(Thr917Met) (c.2750C > T) (rs1165711448) of the CHD7 (Chromodomain-helicase-DNA-binding protein 7) gene was found [30]; it was confirmed by Sanger sequencing, and the variant with uncertain pathogenic significance p.(Ala369Val) c.1106C > T (rs771836971) in FLRT3 (Fibronectin Leucine Rich Transmembrane Protein 3) gene, both in heterozygosity.

2.4. Case 4

Case 4 was a 36-year-old male patient searching for fatherhood in the last 3 years. The female partner had a child from a previous marital relationship and a female factor infertility was excluded. Physical examination was unremarkable, with no sign of hypo-androgenization or genital malformation. FSH serum levels were 4.1 IU/mL, luteinizing hormone (LH) 3.6 IU/mL, and total testosterone 5.7 ng/mL. At ultrasound, right and left testicular volumes were 14.1 mL and 14.9 mL, respectively. The patient underwent sperm analysis for 4 time that showed oligozoospermia and teratozoospermia (mean sperm concentration 7.6 million/mL, mean total sperm count 21.5 million/ejaculate, sperm with normal morphology 3%). Acquired causes of oligozoospermia were carefully excluded. The patient was then suspected of a defect of primary spermatogenic failure due to mutation in single genes. The pathogenic variant p.(Ala351Val) c.1052C > T (rs759071081) of the NR5A1 (Nuclear Receptor Subfamily 5 Group A Member 1) gene [31] was found in heterozygosity by NGS.

2.5. Case 5

Case 5 was a 39-year-old patient counseled for primary male infertility. His wife and he had searched for childhood in the last two years. The patient’s wife was 35 years old and no female factor infertility was found. The physical examination of the patient was unremarkable, with normal androgenization and no sign of genital malformation. FSH serum levels were above the normal range (17.5 IU/mL) and, at ultrasound, the right and the left testicular volumes were 6.3 mL and 9.8 mL, respectively, indicating testicular hypotrophy. Two sperm analyses showed 11.5 million/mL for sperm concentration, 11.5 million/ejaculate for total sperm count, 7.5% for progressive motility, 50% for total motility, and 5.5% spermatozoa with normal morphology. These values indicated a diagnosis of oligoasthenozoospermia. After acquired causes were excluded, the patient underwent to genetic testing for the suspicious of primary spermatogenic failure due to mutation in single genes. The genetic test revealed the pathogenic variant in NR5A1 gene p.(Val355Met) (c.1063G > A) (rs371701248) [31] in heterozygosity and other two not pathogenic variants: p.(Arg323Cys) c.967C > T (rs764712886) in SEPT12 gene and p.(Ile2226Val) (c.6676A > G) (rs112505934) in DNAH1 gene. Interestingly, one year later, the patient spontaneously made his wife pregnant.
The coverage performance by NGS for these subjects is shown in Table 2. Coding genomic regions that were sequenced with a coverage less than 10X were eventually re-sequenced using Sanger technology.

3. Discussion

Male infertility can be the result of non-genetic or genetic factors, and it is often multifactorial and/or polygenic [32]. Hundreds of genes implicated in the development and function of the male reproductive system and in spermatogenesis can be involved [33]. Additional genetic anomalies contributing to male infertility are constantly identified. The process of evaluating the genes involved in male infertility is essential to optimize genetic testing in reproductive medicine and to implement the therapeutic management based on the specific genomic features of the patient. Interestingly, clinicians can more accurately decide whether male infertile patients are candidates for surgical retrieval of spermatozoa for use in assisted fertilization techniques by the knowledge of the nature of the genetic variants [34]. Studies of identification of relevant mutations and polymorphisms by NGS screening technologies can be used for this purpose and easily incorporated into the clinical practice. Moreover, NGS technologies have made it possible to compact one or more tests into a single NGS-based analysis, thus reducing diagnostic costs and time [35].
We have successfully developed a genetic test based on NGS that covers the main male infertility causes [25,36,37,38]. We have analyzed a custom-made panel of 110 genes in 22 infertile patients (Table 3).
Five of them with suspicion of primary spermatogenesis failure, central hypogonadism, and primary ciliary dyskinesia resulted positive at the diagnostic test. Five variants with a clearly known pathogenic role were identified in TEX11, CCDC39, CHD7, and NR5A1 genes. TEX11 (Testis-expressed gene 11), mapping on the Xq13.1 chromosome, is a X-linked gene essential for meiotic recombination and chromosomal synapsis expressed only in male germ cells [39,40]. The role of TEX11 in spermatogenesis has been recognized in knock-out mouse models and humans [28,41]. Currently, 47 TEX11 variants are known, including 25 variants in azoospermic male and 22 variants in fertile subjects [28]. CCDC39 (Coiled-Coil Domain-Containing 39), mapping on the chromosome 3q26.33, encodes for a protein involved in the motility of cilia and flagella. In particular, variations of CCDC39 gene cause defects in the assembly of the nexin-dynein regulatory complex and inner dynein arms, and disruption of this periodicity. Axonemal disorganization and inner dynein arm defects represent about 12% of all primary ciliary dyskinesia cases [42]. CHD7 is a gene, mapping on the 8q12.2 chromosome, associated with the CHARGE syndrome. It overlaps with Kallmann syndrome and central hypogonadism, since affects patients that show gonadotropin deficiency, showing that this gene is involved in puberty and reproduction [43]. Almost all de novo variants in CHD7 occur in the paternal germline [44,45]. Finally, NR5A1 (steroidogenic factor-1), a member of the nuclear receptor superfamily mapping on the chromosome 9q33.3, is a key transcriptional regulator of genes involved in the hypothalamic-pituitary-steroidogenic axis [46,47]. In mammalian testis determination and differentiation, NR5A1 is a positive regulator of SOX9 gene and anti-Müllerian hormone [48]. About 4% of patients with otherwise unexplained severe spermatogenic failure carry variants in NR5A1 [49]. Variants of this gene are also a genetic cause of severer forms of male factor infertility, especially when associated with a history of cryptorchidism [50].
The pathogenic variants identified in these genes were reported in NCBI and their causal role has been shown by functional studies [29,30,31,32]. In particular, two of these variants in homozygosis were identified in TEX11 gene in case 1 (c.2288T > C and c.776C > T), of which one pathogenic and another likely benign. The pathogenic variant c.2288T > C identified in case 1 has been described in the literature in association with azoospermia with functional studies [29].
Three variants of CCDC39 gene in heterozygosity were identified in the case 2. The c.610-2A> G variant was considered pathogenic since it alters a splicing acceptor site and has already been reported in the literature associated with the subject’s condition [29]. c.2431C > T variant was of uncertain pathogenic significance because it has not been reported in the literature in association with pathological phenotypes and it affects a conserved residue of the protein altering its nature. Finally, the CCDC39 c.545C > G variation was a benign variant.
Case 3 was found to be carrier of variants in CHD7 gene. The heterozygous variant c.2750C > in CHD7 is a missense variant in a gene region coding for a “critical” portion of the protein whose involvement has already been to be pathogenic [30,36], and it is a variant considered “likely pathogenic” in most of the simulation programs selected for interpretive use. Other pathogenic variants were identified in NR5A1 gene that is notoriously involved in male infertility. In particular, 2 heterozygous variants in NR5A1 gene were found in two patients suspected of having a defect of primary spermatogenesis due to mutation in single genes: c.1052C > T in the case 4 and c.1063G > A in the case 5. Case 4 carried the c.1052C > T variant that affects a conserved residue of the protein located in a functional domain. This variant was reported in a patient with bilateral anorchia, in a functional study that demonstrates its reduced transcriptional activity. Furthermore, a segregation study showed that it was also present in the healthy relatives, suggesting a possible effect of incomplete penetrance [32]. Instead, the variation c.1063G > A identified in the case 5 affects a conserved protein residue but not altering its nature. It is in a functional domain of the protein and it has already been reported in the literature in a case of disorders of sexual development [31]. Noteworthy, a different variation of the same codon was reported in association with disorders of sexual development with male karyotype (sex reversal) with functional supporting studies that show that the variant alters a domain functional protein [51].
NGS-based genetic screening of a large panel of genes increases the number of novel variants and variants of uncertain pathogenic significance [52]. In this study, 4 splice variants (c.2316 + 1G > A in CATSPER1, c.1600-1G > A in DRC1, c.2427 + 1G > A in HFM1, c.325 + 2T > C in USP9Y) and 3 missense variants (c.2500A > T in AR, c.5805G > C in DNAH11 and c.907T > C in TUBB8) predicted in silico as probably deleterious were identified (ST1); however more data are needed to demonstrate their pathogenicity. Therefore, we did not report them in the results section. Surely, they warrant further studies in the future. Among variants with an uncertain pathogenic role, 14 with uncertain pathogenic significance were identified in this study. In the three positive cases, the variants with uncertain pathogenic significance c.776C > T in TEX1 and c.50G > C in ZBPB, c.2431C > T in CCDC3 and c.614C > T in CDC151, c.1106C > T in FLRT3 were, respectively, identified. In other patients examined, c.6173C > T in DNAH11, c.1960C > T in DNAI1, c.854C > T in DNAI2, c.17G > A in PLK4 variants with uncertain pathogenic significance and c.2159G > A in GLI2 and c.1331C > T in LRRC6 variants with conflicting interpretations of pathogenicity were found. Although including variant of unknown significance (VUS) as decisive results of phenotype in routine clinical elective genetic testing is not recommended, it is recognized that clinical information provided with the sample may give significance to the VUS variants. Anyway, functional studies and segregation studies in other family members could shed light on the clinical significance of novel and with uncertain pathogenic significance variants. Other variants identified were very interesting but it is necessary a functional and segregation family study for these variants, for instance a frameshift variant c.3792_3793del (rs778085976) in CENPF, a stop lost variant c.417A > G (rs1429366684) in KISS1 and numerous splice variants (Supplementary Table S1). Because some cases of male infertility are due to unknown genetic variants, the detection of numerous genetic variants by NGS-based genetic screening is important to reduce the percentage of idiopathic infertility.
Genetic analysis is generally performed using many different platforms. The use of a NGS custom panel is advantageous because it allows the identification of variants by a single platform with optimal sensitivity and specificity. However, there are some limitations. For instance, the NGS custom-made panel cannot detect balanced translocations, which are known to cause infertility in 0.9% of patients and complex chromosomal rearrangements in infertile male patients [53,54]. Anyway, the NGS custom-made panel developed in this study had the ability to provide detailed information that help the clinical management of the infertile male.
In conclusion, our study showed the efficacy of an NGS-based approach in the diagnosis of male infertility according to the patient’s clinical features. In fact, for patients with suspect and established diagnosis of male infertility obtained by first/second level diagnostic tests, it is of pivotal importance to use a genetic test in the attempt of explaining the underlying etiology of the disorder and guide the clinical management. Our gene panel solved the 22% (5/22) of cases considered with apparently idiopathic infertility. This is relevant since the prevalence of idiopathic male infertility has been esteemed as high as the ~70% when panels currently available in the clinical practice are used [55]. Hence, the prevalence could be lower if properly tested with advanced gene panels.
In conclusion, for the patients with a negative diagnosis we could not determine the causative mutations and more studies are needed to evaluate whether the VUS we identified can have an effect on the observed phenotype or other genes should be investigated. Finally, it is not possible to establish phenotypic parameters that would suggest a genetic involvement. Therefore, it is useful to perform genetic testing in all idiopathic infertility cases, regardless of the severity.

4. Materials and Methods

4.1. Patients and Blood Samples

Twenty-two subjects with a clinical diagnosis of male infertility were selected for this study. All enrolled patients underwent pre-test counseling during which they were informed about the significance of molecular screening providing information about their personal and familial history, and informed consent was obtained from each subject. The study was conducted in accordance with the tenets of the Declaration of Helsinki and it was approved by the local Ethics Committee. A blood EDTA (Ethylenediaminetetraacetic acid) sample was collected from each subject. Samples of genomic DNA of all subjects were extracted from peripheral blood using a commercial kit (SAMAG 120 BLOOD DNA Extraction Kit, Como, Italy). DNA was quantified using Quant-iT Picogreen dsDNA Assay Kit (Invitrogen, Eugene, OR) and a Varioskan LUX (Thermo Scientific, Vantaa Finland).

4.2. Gene Selection and Panel Design

A NGS panel consisting of 110 diagnostic genes related to male infertility disorders was designed. The genes included in the panel were based on their correlation with male infertility described in OMIM [17], GeneReviews [56] and primary literature. For each subject, only the genes related to the diagnostic suspect were considered because the analysis was for diagnostic purposes. The custom Illumina Nextera panel included genomic targets comprising coding exons and 15 bp flanking regions of each genes. The list of genes associated with male infertility included in the NGS panel broken down by diagnostic suspect is shown in Table 4. The association of diagnostic suspects with their etiology is shown in the Supplementary Tables (ST2, ST3, ST4, ST5, ST6). The cumulative target length of the gene panel was 314,814 bp. For each diagnostic suspect the size target was respectively: 93,474 bp, 59,379 bp, 3003 bp, 12,729 bp and 162,534 bp.

4.3. Genetic Analysis and Variant Detection

DNA samples were processed for library preparation targeted capture and sequencing as previous reported [57,58]. In particular, 150 bp paired-end reads sequencing was performed on MiSeq personal sequencer (Illumina, San Diego, CA) according to the manufacturer’s instructions. Fastq (forward-reverse) files were obtained after sequencing. Reads alignment was done by the BWA (0.7.17-r1188) software. Duplicates were removed using the SAMBAMBA (0.6.7) program and GATK (4.0.0.0) were used for re-alignment. We used international databases dbSNP (www.ncbi.nlm.nih.gov/SNP/) and Human Gene Mutation Database professional (HGMD; http://www.biobase international.com/product/hgmd) for all nucleotide changes. In silico evaluation of the pathogenicity of nucleotide changes in exons was performed using PolyPhen-2 (http://genetics.bwh.harvard.edu/pph2/), SIFT (https://sift.bii.a-star.edu.sg/), and Mutation Taster (http://www. mutationtaster.org). Minor allele frequencies (MAF) were checked in the Genome Aggregation Database (gnomAD (http://gnomad.broadinstitute.org/)). Sanger sequencing was performed for confirmation when target region coverage was less than 10 reads. Nucleotide alterations were analyzed and validated by Sanger sequencing. After confirmation, each variant was classified as pathogenic, likely pathogenic, VUS, likely benign, or benign, in according to the American College of Medical Genetics (ACMG) guidelines [59]. Variants were considered causative when at least 2 predictors evaluated the variants as damaging and/or there were literature data that demonstrated the pathogenicity.

Supplementary Materials

The following are available online at https://www.mdpi.com/2075-1729/10/10/242/s1, Table S1: Genetic variants identified in the analysed population by NGS. 1 All identified variants are indicated both by cDNA base sequence (third column) and by protein sequence (fourth column) according to the HGVS (Human Genome Variation Society) nomenclature guidelines.2 Information reported in NCBI (National Centre for Biotechnology Information) database, Table S2: List of defects of primary spermatogenesis due to mutation in single genes and their genetic etiology, Table S3: List of hypogonadotropic hypogonadism and their genetic etiology, Table S4: List of primary ciliary dyskinesia and their genetic etiology, Table S5: List of androgen insensitivity and their genetic etiology, Table S6: List of congenital hypopituitarism and their genetic etiology.

Author Contributions

Conceptualization, M.B. and A.E.C.; Data curation, R.C., V.P., G.G., G.M.B., G.C.D.R., S.G., E.M., A.E.C., A.D.; methodology, G.G.; Investigation, V.P., R.C.; Writing—original draft, V.P.; Funding acquisition, M.B. Project administration, M.B. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by funding from the Provincia Autonoma di Trento within the initiative LP6/99 (dpg 1045/2017).

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Pereira, R.; Sá, R.; Barros, A.; Sousa, M. Major regulatory mechanisms involved in sperm motility. Asian J. Androl. 2015, 19, 5–14. [Google Scholar] [CrossRef] [PubMed]
  2. Vanaken, G.J.; Bassinet, L.; Boon, M.; Mani, R.; Honoré, I.; Papon, J.-F.; Cuppens, H.; Jaspers, M.; Lorent, N.; Coste, A.; et al. Infertility in an adult cohort with primary ciliary dyskinesia: Phenotype–gene association. Eur. Respir. J. 2017, 50, 1700314. [Google Scholar] [CrossRef] [PubMed]
  3. Pereira, R.; Oliveira, M.E.; Santos, R.; Oliveira, E.; Barbosa, T.; Santos, T.; Gonçalves, P.; Ferraz, L.; Pinto, S.; Barros, A.; et al. Characterization of CCDC103 expression profiles: Further insights in primary ciliary dyskinesia and in human reproduction. J. Assist. Reprod. Genet. 2019, 36, 1683–1700. [Google Scholar] [CrossRef] [PubMed]
  4. Shu, J.-H.; Feng, G.; Li, J.; Li, J.-X.; Gan, X.-Y.; Zhang, B.; Zhou, H.; Liu, Y. Predictive value of sperm morphology according to WHO Laboratory Manual for the Examination and Processing of Human Semen (5th Ed) on the outcomes of IVF-ET. Zhonghua nan ke xue Natl. J. Androl. 2013, 19, 414–417. [Google Scholar]
  5. Coutton, C.; Fissore, R.A.; Palermo, G.D.; Stouffs, K.; Touré, A. Male Infertility: Genetics, Mechanism, and Therapies. BioMed Res. Int. 2016, 2016, 7372362. [Google Scholar] [CrossRef]
  6. Zorrilla, M.; Yatsenko, A.N. The Genetics of Infertility: Current Status of the Field. Curr. Genet. Med. Rep. 2013, 1, 247–260. [Google Scholar] [CrossRef] [Green Version]
  7. Matzuk, M.M.; Lamb, D.J. The biology of infertility: Research advances and clinical challenges. Nat. Med. 2008, 14, 1197–1213. [Google Scholar] [CrossRef]
  8. Semple, R.K.; Topaloglu, A.K. The recent genetics of hypogonadotrophic hypogonadism–novel insights and new questions. Clin. Endocrinol. 2010, 72, 427–435. [Google Scholar] [CrossRef]
  9. McPhaul, M.J.; Marcelli, M.; Zoppi, S.; Wilson, C.M.; Griffin, J.E.; Wilson, J.D. Mutations in the ligand-binding domain of the androgen receptor gene cluster in two regions of the gene. J. Clin. Investig. 1992, 90, 2097–2101. [Google Scholar] [CrossRef] [Green Version]
  10. Damseh, N.; Quercia, N.; Rumman, N.; Dell, S.D.; Kim, R.H. Primary ciliary dyskinesia: Mechanisms and management. Appl. Clin. Genet. 2017, 10, 67–74. [Google Scholar] [CrossRef] [Green Version]
  11. Parks, J.S. Congenital Hypopituitarism. Clin. Perinatol. 2018, 45, 75–91. [Google Scholar] [CrossRef] [PubMed]
  12. Forti, G.; Krausz, C. Clinical review 100: Evaluation and treatment of the infertile couple. J. Clin. Endocrinol. Metab. 1998, 83, 4177–4188. [Google Scholar] [PubMed]
  13. Sikka, S.C.; Hellstrom, W.J. Current updates on laboratory techniques for the diagnosis of male reproductive failure. Asian, J. Androl. 2016, 18, 392–401. [Google Scholar] [CrossRef] [PubMed]
  14. Xavier, M.J.; Salas-Huetos, A.; Oud, M.S.; Aston, K.I.; Veltman, J.A. Disease gene discovery in male infertility: Past, present and future. Qual. Life Res. 2020, 1–13. [Google Scholar] [CrossRef]
  15. Cannarella, R.; Condorelli, R.A.; Paolacci, S.; Barbagallo, F.; Guerri, G.; Bertelli, M.; La Vignera, S.; Calogero, A.E. Next-generation sequencing: Toward an increase in the diagnostic yield in patients with apparently idiopathic spermatogenic failure. Asian, J. Androl. 2020. [Google Scholar] [CrossRef]
  16. Cannarella, R.; Condorelli, R.A.; Duca, Y.; La Vignera, S.; Calogero, A.E. New insights into the genetics of spermatogenic failure: A review of the literature. Qual. Life Res. 2019, 138, 125–140. [Google Scholar] [CrossRef]
  17. Amberger, J.S.; Bocchini, C.A.; Schiettecatte, F.J.M.; Scott, A.F.; Hamosh, A. OMIM.org: Online Mendelian Inheritance in Man (OMIM®), an online catalog of human genes and genetic disorders. Nucleic Acids Res. 2015, 43, D789–D798. [Google Scholar] [CrossRef] [Green Version]
  18. Bracke, A.; Peeters, K.; Punjabi, U.; Hoogewijs, D.; Dewilde, S. A search for molecular mechanisms underlying male idiopathic infertility. Reprod. Biomed. Online 2018, 36, 327–339. [Google Scholar] [CrossRef] [Green Version]
  19. Cariati, F.; Savarese, M.; D’Argenio, V.; Salvatore, F.; Tomaiuolo, R. The SEeMORE strategy: Single-tube electrophoresis analysis-based genotyping to detect monogenic diseases rapidly and effectively from conception until birth. Clin. Chem. Lab. Med. 2017, 56, 40–50. [Google Scholar] [CrossRef]
  20. Griffin, D.K.; Ogur, C. Chromosomal analysis in IVF: Just how useful is it? Reproduction 2018, 156, F29–F50. [Google Scholar] [CrossRef]
  21. Cariati, F.; D’Argenio, V.; Tomaiuolo, R. The evolving role of genetic tests in reproductive medicine. J. Transl. Med. 2019, 17, 267. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Cooper, T.G.; Noonan, E.; Von Eckardstein, S.; Auger, J.; Baker, H.W.G.; Behre, H.M.; Haugen, T.B.; Kruger, T.; Wang, C.; Mbizvo, M.T.; et al. World Health Organization reference values for human semen characteristics*‡. Hum. Reprod. Updat. 2009, 16, 231–245. [Google Scholar] [CrossRef] [PubMed]
  23. Krausz, C.; Riera-Escamilla, A. Genetics of male infertility. Nat. Rev. Urol. 2018, 15, 369–384. [Google Scholar] [CrossRef] [PubMed]
  24. Oud, M.S.; Volozonoka, L.; Smits, R.M.; Vissers, L.E.L.M.; Ramos, L.; Veltman, J.A. A systematic review and standardized clinical validity assessment of male infertility genes. Hum. Reprod. 2019, 34, 932–941. [Google Scholar] [CrossRef] [Green Version]
  25. Kusz-Zamelczyk, K.; Tomczyk, L.; Sajek, M.P.; Spik, A.; Latos-Bielenska, A.; Jedrzejczak, P.; Pawelczyk, L.; Jaruzelska, J. The highly conserved NANOS2 protein: Testis-specific expression and significance for the human male reproduction. Mol. Hum. Reprod. 2009, 15, 165–171. [Google Scholar] [CrossRef] [Green Version]
  26. Jedidi, I.; Ouchari, M.; Yin, Q. Autosomal single-gene disorders involved in human infertility. Saudi, J. Biol. Sci. 2017, 25, 881–887. [Google Scholar] [CrossRef]
  27. Robay, A.; Abbasi, S.; Akil, A.; El-Bardisi, H.; Arafa, M.; Crystal, R.G.; Crystal, R.G. A systematic review on the genetics of male infertility in the era of next-generation sequencing. Arab. J. Urol. 2018, 16, 53–64. [Google Scholar] [CrossRef] [Green Version]
  28. Yang, F.; Silber, S.; Leu, N.A.; Oates, R.D.; Marszalek, J.D.; Skaletsky, H.; Brown, L.G.; Rozen, S.G.; Page, D.C.; Wang, P.J. TEX 11 is mutated in infertile men with azoospermia and regulates genome-wide recombination rates in mouse. EMBO Mol. Med. 2015, 7, 1198–1210. [Google Scholar] [CrossRef]
  29. Merveille, A.-C.; Davis, E.E.; Becker-Heck, A.; Legendre, M.; Amirav, I.; Bataille, G.; Belmont, J.; Beydon, N.; Billen, F.; Clément, A.; et al. CCDC39 is required for assembly of inner dynein arms and the dynein regulatory complex and for normal ciliary motility in humans and dogs. Nat. Genet. 2010, 43, 72–78. [Google Scholar] [CrossRef]
  30. Bartels, C.F.; Scacheri, C.; White, L.; Scacheri, P.C.; Bale, S. Mutations in the CHD7 Gene: The Experience of a Commercial Laboratory. Genet. Test. Mol. Biomark. 2010, 14, 881–891. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  31. Philibert, P.; Zenaty, D.; Lin, L.; Soskin, S.; Audran, F.; Léger, J.; Achermann, J.C.; Sultan, C. Mutational analysis of steroidogenic factor 1 (NR5a1) in 24 boys with bilateral anorchia: A French collaborative study. Hum. Reprod. 2007, 22, 3255–3261. [Google Scholar] [CrossRef] [PubMed]
  32. Mallepaly, R.; Butler, P.R.; Herati, A.S.; Lamb, D.J.; Vogt, P. Genetic Basis of Male and Female Infertility. Genet. Hum. Infertil. 2017, 21, 1–16. [Google Scholar] [CrossRef]
  33. Mobasheri, M.B.; Babatunde, K. Testicular miRNAs in relation to spermatogenesis, spermatogonial stem cells and cancer/testis genes. Sci. Afr. 2019, 3, e00067. [Google Scholar] [CrossRef]
  34. Xiong, H.Y.; Alipanahi, B.; Lee, L.J.; Bretschneider, H.; Merico, D.; Yuen, R.K.C.; Hua, Y.; Gueroussov, S.; Najafabadi, H.S.; Hughes, T.R.; et al. The human splicing code reveals new insights into the genetic determinants of disease. Science 2014, 347, 1254806. [Google Scholar] [CrossRef] [Green Version]
  35. Hopps, C.; Mielnik, A.; Goldstein, M.; Palermo, G.; Rosenwaks, Z.; Schlegel, P. Detection of sperm in men with Y chromosome microdeletions of the AZFa, AZFb and AZFc regions. Hum. Reprod. 2003, 18, 1660–1665. [Google Scholar] [CrossRef] [Green Version]
  36. Neto, F.T.L.; Bach, P.V.; Najari, B.B.; Li, P.S.; Goldstein, M. Genetics of Male Infertility. Curr. Urol. Rep. 2016, 17, 1–12. [Google Scholar] [CrossRef]
  37. Miyamoto, T.; Minase, G.; Shin, T.; Ueda, H.; Okada, H.; Sengoku, K. Human male infertility and its genetic causes. Reprod. Med. Biol. 2017, 16, 81–88. [Google Scholar] [CrossRef]
  38. Adelman, C.A.; Petrini, J.H. ZIP4H (TEX11) Deficiency in the Mouse Impairs Meiotic Double Strand Break Repair and the Regulation of Crossing Over. PLoS Genet. 2008, 4, e1000042. [Google Scholar] [CrossRef] [Green Version]
  39. Yatsenko, A.N.; Georgiadis, A.P.; Röpke, A.; Berman, A.J.; Jaffe, T.; Olszewska, M.; Westernströer, B.; Sanfilippo, J.; Kurpisz, M.; Rajkovic, A.; et al. X-Linked TEX11 Mutations, Meiotic Arrest, and Azoospermia in Infertile Men. N. Engl. J. Med. 2015, 372, 2097–2107. [Google Scholar] [CrossRef] [Green Version]
  40. Zheng, K.; Yang, F.; Wang, P.J. Regulation of male fertility by X-linked genes. J. Androl. 2009, 31, 79–85. [Google Scholar] [CrossRef]
  41. Sha, Y.; Zheng, L.; Ji, Z.; Mei, L.; Ding, L.; Lin, S.; Wang, X.; Yang, X.; Li, P. A novel TEX11 mutation induces azoospermia: A case report of infertile brothers and literature review. BMC Med. Genet. 2018, 19, 63. [Google Scholar] [CrossRef] [Green Version]
  42. Antony, D.; Becker-Heck, A.; Zariwala, M.A.; Schmidts, M.; Onoufriadis, A.; Forouhan, M.; Wilson, R.; Taylor-Cox, T.; Dewar, A.; Jackson, C.; et al. Mutations inCCDC39andCCDC40are the Major Cause of Primary Ciliary Dyskinesia with Axonemal Disorganization and Absent Inner Dynein Arms. Hum. Mutat. 2013, 34, 462–472. [Google Scholar] [CrossRef] [Green Version]
  43. Balasubramanian, R.; Crowley, W.F. Reproductive endocrine phenotypes relating toCHD7mutations in humans. Am. J. Med. Genet. Part. C Semin Med. Genet. 2017, 175, 507–515. [Google Scholar] [CrossRef] [Green Version]
  44. Pauli, S.; Von Velsen, N.; Burfeind, P.; Steckel, M.; Manz, J.; Buchholz, A.; Borozdin, W.; Kohlhase, J. CHD7 mutations causing CHARGE syndrome are predominantly of paternal origin. Clin. Genet. 2011, 81, 234–239. [Google Scholar] [CrossRef]
  45. Bouazoune, K.; Kingston, R.E. Chromatin remodeling by the CHD7 protein is impaired by mutations that cause human developmental disorders. Proc. Natl. Acad. Sci. USA 2012, 109, 19238–19243. [Google Scholar] [CrossRef] [Green Version]
  46. Morohashi, K.; Honda, S.; Inomata, Y.; Handa, H.; Omura, T. A common trans-acting factor, Ad4-binding protein, to the promoters of steroidogenic P-450s. J. Biol. Chem. 1992, 267, 17913–17919. [Google Scholar]
  47. Lin, L.; Achermann, J.C. Steroidogenic factor-1 (SF-1, Ad4BP, NR5A1) and disorders of testis development. Sex. Dev. 2008, 2, 200–209. [Google Scholar] [CrossRef] [Green Version]
  48. Sekido, R.; Lovell-Badge, R. Sex determination involves synergistic action of SRY and SF1 on a specific Sox9 enhancer. Nat. Cell Biol. 2008, 453, 930–934. [Google Scholar] [CrossRef]
  49. Bashamboo, A.; Ferraz-De-Souza, B.; Lourenço, D.; Lin, L.; Sebire, N.J.; Montjean, D.; Bignon-Topalovic, J.; Mandelbaum, J.; Siffroi, J.-P.; Christin-Maitre, S.; et al. Human Male Infertility Associated with Mutations in NR5A1 Encoding Steroidogenic Factor 1. Am. J. Hum. Genet. 2010, 87, 505–512. [Google Scholar] [CrossRef] [Green Version]
  50. Ferlin, A.; Rocca, M.S.; Vinanzi, C.; Ghezzi, M.; Di Nisio, A.; Foresta, C. Mutational screening of NR5A1 gene encoding steroidogenic factor 1 in cryptorchidism and male factor infertility and functional analysis of seven undescribed mutations. Fertil. Steril. 2015, 104, 163–169.e1. [Google Scholar] [CrossRef]
  51. Rocca, M.S.; Ortolano, R.; Menabò, S.; Baronio, F.; Cassio, A.; Russo, G.; Balsamo, A.; Ferlin, A.; Baldazzi, L. Mutational and functional studies on NR5A1 gene in 46,XY disorders of sex development: Identification of six novel loss of function mutations. Fertil. Steril. 2018, 109, 1105–1113. [Google Scholar] [CrossRef] [PubMed]
  52. Harper, J.C.; Aittomäki, K.; Borry, P.; Cornel, M.C.; De Wert, G.; Dondorp, W.; Geraedts, J.; Gianaroli, L.; Ketterson, K.; Liebaers, I.; et al. Recent developments in genetics and medically assisted reproduction: From research to clinical applications. Eur. J. Hum. Genet. 2017, 26, 12–33. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Mau-Holzmann, U. Somatic chromosomal abnormalities in infertile men and women. Cytogenet. Genome Res. 2005, 111, 317–336. [Google Scholar] [CrossRef] [PubMed]
  54. Kim, J.-W.; Chang, E.M.; Song, S.H.; Park, S.H.; Yoon, T.K.; Shim, S.H. Complex chromosomal rearrangements in infertile males: Complexity of rearrangement affects spermatogenesis. Fertil. Steril. 2011, 95, 349–352. [Google Scholar] [CrossRef] [PubMed]
  55. Punab, M.; Poolamets, O.; Paju, P.; Vihljajev, V.; Pomm, K.; Ladva, R.; Korrovits, P.; Laan, M. Causes of male infertility: A 9-year prospective monocentre study on 1737 patients with reduced total sperm counts. Hum. Reprod. 2016, 32, 18–31. [Google Scholar] [CrossRef]
  56. GeneReviews® [Internet]; Adam, M.P.; Ardinger, H.H.; Pagon, R.A.; Wallace, S.E.; Bean, L.J.H.; Stephens, K.; Amemiya, A. (Eds.) University of Washington: Seattle, WA, USA, 1993–2020.
  57. Mattassi, R.; Manara, E.; Colombo, P.G.; Manara, S.; Porcella, A.; Bruno, G.; Bruson, A.; Bertelli, M. Variant discovery in patients with Mendelian vascular anomalies by next-generation sequencing and their use in patient clinical management. J. Vasc. Surg. 2018, 67, 922–932.e11. [Google Scholar] [CrossRef] [Green Version]
  58. Marceddu, G.; Dallavilla, T.; Guerri, G.; Zulian, A.; Marinelli, C.; Bertelli, M. Analysis of machine learning algorithms as integrative tools for validation of next generation sequencing data. Eur. Rev. Med. Pharmacol. Sci. 2019, 23, 8139–8147. [Google Scholar]
  59. Richards, S.; Aziz, N.; Bale, S.; Bick, D.; Das, S.; Gastier-Foster, J.; Grody, W.W.; Hegde, M.; Lyon, E.; Spector, E.; et al. ACMG Laboratory Quality Assurance Committee. Standards and guidelines for the interpretation of sequence variants: A joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet. Med. 2015, 17, 405–424. [Google Scholar]
Table
Table 1. Variants identified in the patients with a positive genetic diagnosis.
Table 1. Variants identified in the patients with a positive genetic diagnosis.
CaseGene (Transcript Isoform)Variant PositionVariantZygositySNP IDPolyphen-2SIFTMutation TasterMAF (%)Ref
1TEX11 (NM_001003811.1)chrX:70554698c.2288T > C; p.Val763AlaHemrs200139216BenignDamagingPolymorphism0.02%[28]
2CCDC39 (NM_181426.1)chr3:180616671c.2431C > T; p.Arg811CysHetrs574993914Probably damagingDamagingDisease-causing0.007%/
chr3:180659582c.610–2A > GHetrs756235547//Disease-causing0.01%[29]
3CHD7 (NM_017780.3)chr8:60821842c.2750C > T; p.Thr917MetHetrs1165711448Probably damagingDamagingDisease-causing/[30]
4NR5A1 (NM_004959.4)chr9:124491167c.1052C > T; p.Ala351ValHetrs759071081Probably damagingToleratedDisease-causing0.005%[31]
5NR5A1 (NM_004959.4)chr9:124491156c.1063G > A; p.Val355MetHetrs371701248Probably damagingDamagingDisease-causing0.01%[31]
Table
Table 2. NGS Coverage performance for positive subjects of the diagnostic test.
Table 2. NGS Coverage performance for positive subjects of the diagnostic test.
Medium CoverageCoverage >10X
Case 1317.7X98.5%
Case 2296.5X98.7%
Case 3539.2X98.9%
Case 4296.5X98.7%
Case 5286.7X91.3%
Table
Table 3. Available clinical characteristics of all the analyzed patients. Abbreviations: FSH, follicle-stimulating hormone; * evaluated with ultrasound; ** values before therapy.
Table 3. Available clinical characteristics of all the analyzed patients. Abbreviations: FSH, follicle-stimulating hormone; * evaluated with ultrasound; ** values before therapy.
Diagnostic SuspectSperm ParametersFSH (IU/L)Mean Testicular Volume (mL) *Additional Data
Case 1Primary spermatogenic defectsOligoasthenozoospermia (6.6 mil/ejac)8.114.4//
Case 2Primary ciliary dyskinesiaAzoospermia, then oligoasthenoteratozoospermia after scleroembolizationUnavailableUnavailableRight varicocele, dextrocardia, bronchiectasia, abnormal connecting piece, and absence of outer dynein arms in the sperm axoneme, abnormal number and position of peripheral microtubules and central pair in the respiratory cilia
Case 3Central hypogonadismSevere oligoasthenoteratozoospermiaUnavailable5.4Low gonadotropins, treated with testosterone replacement therapy, severe left varicocele
Case 4Primary spermatogenic defectsOligoteratozoospermia (21.5 mil/ejac)4.114.5//
Case 5Primary spermatogenic defectsOligoasthenozoospermia (11.5 mil/ejac)17.58Testicular hypotrophy
Case 6Primary spermatogenic defectsSevere oligoasthenoteratozoospermia (<5 mil/ejac)6.1112.7The patient was treated with FSH to increase the sperm number, but was unresponsive
Case 7Primary spermatogenic defectsUnavailableUnavailableUnavailable//
Case 8Primary spermatogenic defectsAzoospermia3.2414.8The patient was counseled for testicular sperm extraction, with no result
Case 9Congenital hypopituitarismAzoospermia **1.67 **12.0The patient was counseled for therapy with gonadotropins. The couple opted for ART (Assisted Reproductive Technology) using sperm of a donor. Hence, testosterone was prescribed
Case 10Primary spermatogenic defectsMild oligozoospermia3.7711.6//
Case 11Primary spermatogenic defectsAzoospermia30.96.6Sertoli cell only syndrome was found in testicular histology
Case 12Central hypogonadismCriptozoospermia **<0.9 **5.5The patient was responsive to treatment with gonadotropins
Case 13Androgen insensitivityUnavailableUnavailableUnavailableThe patient had abnormally high testosterone serum level. He has normal androgenization
Case 14Primary spermatogenic defectsSevere oligoasthenoteratozoospermia (<5 mil/ejac)2.148.0//
Case 15Primary spermatogenic defectsModerate oligoasthenozoospermia (<15 mil/ejac)6.911.5The patient was unresponsive to treatment with FSH
Case 16Primary spermatogenic defectsUnavailableUnavailableUnavailable//
Case 17Primary spermatogenic defectsUnavailableUnavailableUnavailable//
Case 18Primary spermatogenic defectsUnavailableUnavailableUnavailable//
Case 19Primary spermatogenic defectsUnavailableUnavailableUnavailable//
Case 20Primary spermatogenic defectsUnavailableUnavailableUnavailable//
Case 21Primary spermatogenic defectsUnavailableUnavailableUnavailable//
Case 22Primary spermatogenic defectsUnavailableUnavailableUnavailable//
Table
Table 4. Genes associated with male infertility included in the custom NGS panel.
Table 4. Genes associated with male infertility included in the custom NGS panel.
Male ConditionLocationGenesOMIM #REFSEQGene Name% Target Bases with Coverage ≥ 10X
Defects of primary spermatogenesis19q13.43AURKC603495NM_001015878aurora kinase C100.0%
11q13.1CATSPER1606389NM_053054cation channel sperm associated 1100.0%
3q13.2CFAP44617559NM_018338cilia and flagella-associated protein 44100.0%
12q14.2DPY19L2613893NM_173812dpy-19 like 2100.0%
17q21.2KLHL10608778NM_152467kelch like family member 10100.0%
10q26.11NANOS1608226NM_199461nanos C2HC-type zinc finger 139.45%
22q13.1PICK1605926NM_012407protein interacting with PRKCA 199.75%
4q28.1PLK4605031NM_014264polo like kinase 4100.0%
16p13.3SEPTIN12611562NM_144605septin 12100.0%
9q34.3SOHLH1610224NM_001012415spermatogenesis and oogenesis-specific basic helix-loop-helix 1100.0%
20q11.21SUN5613942NM_080675Sad1 and UNC84 domain-containing 585.74%
12q23.2SYCP3604759NM_001177948synaptonemal complex protein 399.69%
Xp11TEX11300311NM_001003811testis-expressed 1196.43%
Yq11.221USP9Y400005NM_004654ubiquitin specific peptidase 9 Y-linked99.8%
7p12.2ZPBP608498NM_007009zona pellucida binding protein98.08%
1p22.1BRDT602144NM_001726bromodomain testis-associated100.0%
10q25.1CFAP43617558NM_025145cilia and flagella-associated protein 4398.45%
3p21.1DNAH1603332NM_015512dynein axonemal heavy chain 1100.0%
6q22.31HSF2140581NM_004506heat shock transcription factor 2100.0%
16p13.3MEIOB617670NM_152764meiosis specific with OB-fold100.0%
9q33.3NR5A1184757NM_004959nuclear receptor subfamily 5 group A member 1100.0%
12p12.3PLCZ1608075NM_033123phospholipase C zeta 1100.0%
Xq24RHOXF2300447NM_032498Rhox homeobox family member 295.41%
6p21.31SLC26A8608480NM_052961solute carrier family 26 member 8100.0%
3q26.31SPATA16609856NM_031955spermatogenesis associated 16100.0%
10q26.3SYCE1611486NM_130784synaptonemal complex central element protein 1100.0%
18q11.2TAF4B601689NM_005640TATA-box binding protein-associated factor 4b98.17%
8p12TEX15605795NM_001350162testis-expressed 15, meiosis, and synapsis-associated100.0%
17p13.2ZMYND15614312NM_001136046zinc finger MYND-type containing 1592.29%
Hypogonadotropic hypogonadismXp22.31ANOS1300836NM_000216anosmin 195.4%
2q31.2CCDC141616031NM_173648coiled-coil domain-containing 14199.89%
12q21.33DUSP6602748NM_001946dual specificity phosphatase 6100.0%
8p21.3FGF17603725NM_003867fibroblast growth factor 17100.0%
8p11.23FGFR1136350NM_023110fibroblast growth factor receptor 1100.0%
11p14.1FSHB136530NM_000510follicle-stimulating hormone subunit beta100.0%
4q13.2GNRHR138850NM_000406gonadotropin-releasing hormone receptor100.0%
3p14.3IL17RD606807NM_017563interleukin 17 receptor D100.0%
19p13.3KISS1R604161NM_032551KISS1 receptor84.84%
9q34.3NSMF608137NM_015537NMDA receptor synaptonuclear signaling and neuronal migration factor95.03%
3p13PROK2607002NM_021935prokineticin 297.67%
7q21.11SEMA3A603961NM_006080semaphorin 3A100.0%
9q34.3SOHLH1610224NM_001012415spermatogenesis and oogenesis-specific basic helix-loop-helix 1100.0%
5q31.3SPRY4607984NM_030964sprouty RTK-signaling antagonist 498.25%
5q31.3SRA1603819NM_001035235steroid receptor RNA activator 1100.0%
4q24TACR3162332NM_001059tachykinin receptor 3100.0%
19q13.2AXL109135NM_021913AXL receptor tyrosine kinase100.0%
8q12.2CHD7608892NM_017780chromodomain helicase DNA binding protein 799.54%
7q31.32FEZF1613301NM_001024613FEZ family zinc finger 196.46%
10q24.32FGF8600483NM_033163fibroblast growth factor 893.16%
20p12.1FLRT3604808NM_198391fibronectin leucine rich transmembrane protein 3100.0%
8p21.2GNRH1152760NM_001083111gonadotropin-releasing hormone 1100.0%
2q14.3HS6ST1604846NM_004807heparan sulfate 6-O-sulfotransferase 196.3%
1q32.1KISS1603286NM_002256KiSS-1 metastasis suppressor100.0%
19q13.33LHB152780NM_000894luteinizing hormone subunit beta100.0%
20p12.3PROKR2607123NM_144773prokineticin receptor 2100.0%
7q21.11SEMA3E608166NM_012431semaphorin 3E100.0%
22q13.1SOX10602229NM_006941SRY-box transcription factor 10100.0%
12q13.3TAC3162330NM_013251tachykinin precursor 3100.0%
10q26.12WDR11606417NM_018117WD repeat domain 11100.0%
Androgen insensitivityXq12AR313700NM_000044androgen receptor100.0%
Congenital hypopituitarism2q14.2GLI2165230NM_005270GLI family zinc finger 291.92%
9q34.3LHX3600577NM_014564LIM homeobox 381.51%
14q22.3OTX2600037NM_172337orthodenticle homeobox 2100.0%
5q35.3PROP1601538NM_006261PROP paired-like homeobox 195.99%
3p14.3HESX1601802NM_003865HESX homeobox 1100.0%
1q25.2LHX4602146NM_033343LIM homeobox 4100.0%
3p11.2POU1F1173110NM_000306POU class 1 homeobox 1100.0%
Xq27.1SOX3313430NM_005634SRY-box transcription factor 370.12%
Primary ciliary dyskinesia10p12.1ARMC4615408NM_001290020armadillo repeat-containing 499.65%
17q21.31CCDC103614677NM_213607coiled-coil domain-containing 103100.0%
19p13.2CCDC151615956NM_145045coiled-coil domain-containing 15199.13%
17q25.3CCDC40613799NM_017950coiled-coil domain-containing 4098.52%
5q11.2CCNO607752NM_021147cyclin O100.0%
21q22.11CFAP298615494NM_021254cilia and flagella-associated protein 298100.0%
14q21.3DNAAF2612517NM_018139dynein axonemal assembly factor 295.63%
19q13.42DNAAF3614566NM_178837dynein axonemal assembly factor 389.24%
7p22.3DNAAF5614864NM_017802dynein axonemal assembly factor 578.93%
7p15.3DNAH11603339NM_001277115dynein axonemal heavy chain 1199.94%
6p21.2DNAH8603337NM_001206927dynein axonemal heavy chain 899.93%
17q25.1DNAI2605483NM_023036dynein axonemal intermediate chain 2100.0%
14q24.3DNAL1610062NM_031427dynein axonemal light chain 1100.0%
16q24.3GAS8605178NM_001481growth arrest specific 898.09%
8q24.22LRRC6614930NM_012472leucine rich repeat-containing 6100.0%
7p14.1NME8607421NM_016616NME/NM23 family member 8100.0%
21q22.3RSPH1609314NM_080860radial spoke head component 1100.0%
6q22.1RSPH4A612647NM_001010892radial spoke head component 4A100.0%
8q22.2SPAG1603395NM_172218sperm associated antigen 194.7%
17q21.2TTC25617095NM_031421tetratricopeptide repeat domain 2590.46%
3p14.2CFAP20DC300572NM_198463CFAP20 domain-containing100.0%
19q13.33CCDC114615038NM_144577coiled-coil domain-containing 114100.0%
3q26.33CCDC39613798NM_181426coiled-coil domain-containing 39100.0%
12q13.12CCDC65611088NM_033124coiled-coil domain-containing 65100.0%
1q41CENPF600236NM_016343centromere protein F100.0%
16q24.1DNAAF1613190NM_178452dynein axonemal assembly factor 1100.0%
15q21.3DNAAF4608706NM_130810dynein axonemal assembly factor 4100.0%
3p21.1DNAH1603332NM_015512dynein axonemal heavy chain 1100.0%
5p15.2DNAH5603335NM_001369dynein axonemal heavy chain 599.82%
9p13.3DNAI1604366NM_012144dynein axonemal intermediate chain 1100.0%
11q13.4DNAJB13610263NM_153614DnaJ heat shock protein family (Hsp40) member B13100.0%
2p23.3DRC1615288NM_145038dynein regulatory complex subunit 193.24%
16q22.2HYDIN610812NM_001270974HYDIN axonemal central pair apparatus protein98.92%
5q11.2MCIDAS614086NM_001190787multiciliate differentiation and DNA synthesis associated cell cycle protein100.0%
Xq22.3DNAAF6300933NM_001169154dynein axonemal assembly factor 6100.0%
6q25.3RSPH3615876NM_031924radial spoke head 3100.0%
6p21.1RSPH9612648NM_152732radial spoke head component 9100.0%
2q35STK36607652NM_015690serine/threonine kinase 36100.0%
3p21.31ZMYND10607070NM_015896zinc finger MYND-type-containing 10100.0%
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Cannarella, R.; Precone, V.; Guerri, G.; Busetto, G.M.; Di Renzo, G.C.; Gerli, S.; Manara, E.; Dautaj, A.; Bertelli, M.; Calogero, A.E. Clinical Evaluation of a Custom Gene Panel as a Tool for Precision Male Infertility Diagnosis by Next-Generation Sequencing. Life 2020, 10, 242. https://doi.org/10.3390/life10100242

AMA Style

Cannarella R, Precone V, Guerri G, Busetto GM, Di Renzo GC, Gerli S, Manara E, Dautaj A, Bertelli M, Calogero AE. Clinical Evaluation of a Custom Gene Panel as a Tool for Precision Male Infertility Diagnosis by Next-Generation Sequencing. Life. 2020; 10(10):242. https://doi.org/10.3390/life10100242

Chicago/Turabian Style

Cannarella, Rossella, Vincenza Precone, Giulia Guerri, Gian Maria Busetto, Gian Carlo Di Renzo, Sandro Gerli, Elena Manara, Astrit Dautaj, Matteo Bertelli, and Aldo Eugenio Calogero. 2020. "Clinical Evaluation of a Custom Gene Panel as a Tool for Precision Male Infertility Diagnosis by Next-Generation Sequencing" Life 10, no. 10: 242. https://doi.org/10.3390/life10100242

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