A Compound Heterozygous Missense Variant in The DNAH5 Gene Could Be A Significant Factor in Unexplained Male Infertility: A Case Study - PMC Skip to main content An official website of the United States government Here's how you know Here's how you know Official websites use .gov A .gov website belongs to an official government organization in the United States. Secure .gov websites use HTTPS A lock ( Lock Locked padlock icon ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites. Search Log in Dashboard Publications Account settings Log out Search… Search NCBI Primary site navigation Search Logged in as: Dashboard Publications Account settings Log in Search PMC Full-Text Archive Search in PMC Journal List User Guide PERMALINK Copy As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health. Learn more: PMC Disclaimer | PMC Copyright Notice Int J Fertil Steril . 2026 Apr 13;20(2):159–168. doi: 10.22074/ijfs.2025.2051131.1811 Search in PMC Search in PubMed View in NLM Catalog Add to search A Compound Heterozygous Missense Variant in The DNAH5 Gene Could Be A Significant Factor in Unexplained Male Infertility: A Case Study Maryam Afkari Maryam Afkari , Ph.D. 1. Department of Developmental Biology, Faculty of Basic Sciences and Advanced Technologies in Biology, University of Science and Culture, ACECR, Tehran, Iran 2. Department of Genetics, Reproductive Biomedicine Research Center, Royan Institute for Reproductive Biomedicine, ACECR, Tehran, Iran Find articles by Maryam Afkari 1, 2 , Najmeh Salehi Najmeh Salehi , Ph.D. 3. School of Biology, College of Science, University of Tehran, Tehran, Iran Find articles by Najmeh Salehi 3 , Hesamoddin Sajadi Hesamoddin Sajadi , M.D. 4. Department of Andrology, Reproductive Biomedicine Research Center, Royan Institute for Reproductive Biomedicine, ACECR, Tehran, Iran Find articles by Hesamoddin Sajadi 4 , Marjan Sabbaghian Marjan Sabbaghian , Ph.D. 4. Department of Andrology, Reproductive Biomedicine Research Center, Royan Institute for Reproductive Biomedicine, ACECR, Tehran, Iran Find articles by Marjan Sabbaghian 4 , Seyed Abolhassan Shahzadeh-Fazeli Seyed Abolhassan Shahzadeh-Fazeli , M.D., Ph.D. 2. Department of Genetics, Reproductive Biomedicine Research Center, Royan Institute for Reproductive Biomedicine, ACECR, Tehran, Iran 5. Department of Molecular and Cellular Biology, Faculty of Basic Sciences and Advanced Technologies in Biology, University of Science and Culture, ACECR, Tehran, Iran Find articles by Seyed Abolhassan Shahzadeh-Fazeli 2, 5, * , Amir Amiri-Yekta Amir Amiri-Yekta , Ph.D. 2. Department of Genetics, Reproductive Biomedicine Research Center, Royan Institute for Reproductive Biomedicine, ACECR, Tehran, Iran Find articles by Amir Amiri-Yekta 2, * Author information Article notes Copyright and License information 1. Department of Developmental Biology, Faculty of Basic Sciences and Advanced Technologies in Biology, University of Science and Culture, ACECR, Tehran, Iran 2. Department of Genetics, Reproductive Biomedicine Research Center, Royan Institute for Reproductive Biomedicine, ACECR, Tehran, Iran 3. School of Biology, College of Science, University of Tehran, Tehran, Iran 4. Department of Andrology, Reproductive Biomedicine Research Center, Royan Institute for Reproductive Biomedicine, ACECR, Tehran, Iran 5. Department of Molecular and Cellular Biology, Faculty of Basic Sciences and Advanced Technologies in Biology, University of Science and Culture, ACECR, Tehran, Iran * Corresponding Address: P.O.Box: 16635-148 Department of Genetics Reproductive Biomedicine Research Center Royan Institute for Repro ductive Biomedicine ACECR Tehran, Iran Email: [email protected] , [email protected] Received 2025 Jan 19; Revised 2025 Apr 22; Accepted 2025 May 7; Issue date 2026 Apr-Jun. Any use, distribution, reproduction or abstract of this publication in any medium, with the exception of commercial purposes, is permitted provided the original work is properly cited. This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial 3.0 (CC BY-NC 3.0) License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. PMC Copyright notice PMCID: PMC13080711 PMID: 41983364 Abstract Background: Infertility affects approximately 50 million couples worldwide, with both men and women being equally affected. Male infertility is a complex issue with genetic factors playing a significant role. Conditions such as Klinefelter syndrome (XXY), Y chromosome microdeletions (YCMDs), and monogenic mutations can contribute to male infertility. Currently, hereditary factors account for 4% of male infertility cases, while the causes of 60-70% of cases remain unknown. Ongoing research aims to identify new genes and variants related to male fertility to improve diagnostic methods. More than 2000 genes are believed to be involved in preserving germ cells and ensuring normal meiosis, with more than 100 genes already identified for male infertility. Materials and Methods: In this case series study, we assessed a patient with unexplained male infertility, who also had a brother with a similar issue. We used whole exome sequencing (WES) technology, segregation analysis and analyzed the data through bioinformatics tools. Results: Bioinformatics analysis and Sanger sequencing revealed that two infertile brothers had a compound heterozygous (CH) mutation with missense variants in dynein axonemal heavy chain 5 (DNAH5) gene: one variant in exon 9, (c.1121T>C: p.Ile374Thr), and another in exon 66, (c.11437C>T: p.Arg3813Trp). The protein structure analysis showed that the Ile374Thr variant is located near the outer dynein arm-docking subunit 1 (ODA-D1) and ODA-D3. Additionally, the Arg3813Trp variant replaces the positively charged arginine with a hydrophobic tryptophan residue, which may lead to local instability in the protein structure, particularly in the ATP-binding site. Conclusion: Our study reports a CH presence of a missense variant in DNAH5 within a family experiencing male infertility. In silico structural predictions suggest a potential role of these DNAH5 variants in causing fertility issues. Keywords: Bioinformatics, DNAH5 , Unexplained Male Infertility, Whole-Exome Sequencing Introduction Infertility is an inability to conceive after one year of unprotected sex according to the World Health Organiza tion (WHO) definition. Male factors contribute to 50% of infertility cases. Male infertility can be linked to genetic factors in about 15% of cases ( 1 , 2 ). The most common causes are Klinefelter syndrome, chromosomal rearrange ments, Y microdeletions, Kalman syndrome and muta tions in the cystic fibrosis transmembrane conductance regulator (CFTR) gene ( 3 ). Male infertility with undetermined causes can be divided into two categories. The first category is idiopathic male infertility, which means that males are infertile and have abnormal semen analyses (semen volume, sperm count, semen viscosity, sperm morphology, and sperm motility), but no identifiable cause for these abnormalities. The second category is unexplained male infertility, which describes men with normal semen analyses who are unable to conceive for unknown reasons ( 4 ). Sperm flagella are structures that are part of the mobile eukaryotic cilia, which help to propel spermatozoa through the female reproductive system ( 5 ). These mobile flagella and cilia are composed of axoneme that are structured with (9 + 2) microtubules. These microtubules work along with several functional modules to facilitate the movement of these organelles ( 5 , 6 ). Analysis of whole-exome sequencing (WES) has revealed that mutations in genes linked to sperm motility, such as DNAH1 and DNAH5, are commonly found in males with multiple morphological abnormalities of sperm flagella (MMAF) who are experiencing infertility. These mutations account for approximately 34% of all MMAF cases ( 7 , 8 ). The DNAH5 gene (250 kb), located in the 5p15.2 region of the human genome, encodes a heavy-chain protein found on the outer dynein arm (ODA) in the flagellum and cilia structures ( 9 ). The DNAH5 mutations lead to nonfunctional DNAH5 proteins, resulting in dysmotility respiratory cilia with ODA abnormalities. Similarly, ge netic alterations in the DNAI1 gene are responsible for impaired ODA function in individuals with primary cili ary dyskinesia (PCD) ( 10 ). Our study focused on conducting WES analysis on a proband from an Iranian family in order to identify genetic variations linked to unexplained male infertility. The study revealed a connection between the identified genetic variations and the male individuals affected by this condition. After performing the analysis, the findings were confirmed through Sanger sequencing and in silico predictions. Materials and Methods Patient description In this case series study, A 45-year-old man who suffers from infertility (II-4) visited the Royan Infertility Clinic in Tehran, Iran. He has been married for 18 years and has been infertile for a long time without receiving any diagnosis. His sperm parameters are normal and experienced infertility without showing any signs of other conditions, including respiratory symptoms typically associated with PCD. Also, his wife had been under various tests throughout the years, with no indication of any infertility problems and no history of infertility in her pedigree. They had two failed in vitro fertilization (IVF). Genetic counseling revealed that the male individual has a brother, II-6 ( Fig .1 ), who is also unable to conceive. Since the parents (I-1, I-2) are not related, and given the increased likelihood of infertility in the brother (II-6)- who is considered normozoospermia based on semen analysis results (Table 1)-along with the fact that his wife has no family history of infertility, and the inability of normal diagnostic methods to identify the cause of infertility, it has been included individuals II-4 and II-6 as unexplained male infertility. We selected a healthy brother II-7 as a control candidate, along with their parents, for further investigation ( Fig .1 ). All participants completed and signed a written informed consent form, and the Royan Institute Ethics Committee (IR.ACECR.ROYAN. REC.1401.088) approved this study. Fig.1. Open in a new tab Pedigree of an Iranian family with unexplained male infertility. The arrow labeled indicates proband which is patient with infertility. The “-” indicates the wild-type allele. DNA extraction and evaluation As part of our investigation, we collected peripheral blood samples from five individuals using tubes containing Ethylenediaminetetraacetic acid (EDTA, Parspeyvand Co, Iran). We extracted genomic DNA (gDNA) from these samples using the conventional salting-out procedure ( 11 ). The extracted DNA was quantified and purified using a NanoDrop One Spectrophotometer from (Thermo Fisher Scientific, USA). We also examined the integrity of the DNA using agarose gel electrophoresis. The optical density 260/280 ratios of all DNA samples ranged from 1.8 to 2.0. WES was conducted on the gDNA of proband II-4 using the Agilent SureSelect Human All Exon V7 kit (Agilent Technologies, CA, USA). Sequencing libraries were created, indexed, and fragmented into segments ranging from 180 to 280 base pairs using a hydrodynamic shearing system (Covaris, Massachusetts, USA). After blunting the overhangs and removing enzymes, adapter oligonucleotides were ligated, and polymerase chain reaction (PCR) enriched the fragments. Libraries were purified with AMPure XP and quantified with the Agilent Bioanalyzer 2100, then loaded onto NovaSeq 6000 Illumina sequencers. Data quality checking and analysis were conducted on a Unix-based HP server. FastQC version 0.11.8 was used to evaluate the quality of raw sequence reads ( 12 ). The Burrows-Wheeler Alignment (BWA) tool, version 0.7.17-r1188, was then used in MEM mode to align the UCSC human reference genome (GRCh37/hg19 assembly) ( 13 ). The BAM files were sorted, PCR duplicates removed, read groups added, and indexed with Picard-Tools version 1.107 (http://broadinstitute. github.io/picard). Using GATK 4.1.9.0, Base Quality Score Recalibration was performed, followed by variant calling with GATK HaplotypeCaller. The called variants underwent Variant Quality Score Recalibration via GATK VariantRecalibrator ( 14 , 15 ). ANNOVAR was used to annotate the variants from both public and in-house databases ( 16 ). Allele frequencies were analyzed with resources such as dbSNP ( 17 ), the 1000 Genomes Project ( 18 ), ESP ( 19 ), gnomAD ( 20 ), ExAC ( 21 ). In gnomAD version 2.1.1, we excluded variants with MAFs exceeding 0.01. We included exonic and splicesite variants, while excluding intronic, intergenic, and synonymous variants. Therefore, Male infertility panels and published literature on genes associated with male infertility were utilized to identify candidate genes. The effects of the prioritized missense variants were predicted using Mutation Taster, SIFT, PolyPhen2, CADD, DANN, FATHMM, PROVEAN, LRT, M-CAD, MetaSVM, and MetaLR ( 22 ). Additionally, CLUSTAL Omega 1.2.4 (https://www.ebi.ac.uk/jdispatcher/msa/clustalo) was used to assess the evolutionary conservation of the variants in mammals. Polymerase chain reaction-sanger verification To confirm the presence of a genetic variants, oligonucleotide primers flanking the candidate variants were designed by using Primer3plus (http://www.bioinformatics.nl/cgi-bin/primer3plus/primer3plus.cgi) and The NCBI browser (https://www.ncbi.nlm.nih.gov/ gdv/browser/genome) to amplify the specific region by PCR. The primer pairs were then verified using Primer-BLAST (https://www.ncbi.nlm.nih.gov/tools/primer-blast). Standard PCR protocol was followed to amplify the 633-base pair and 550-base pair amplicons for each variant. Sanger direct sequencing was performed using the Applied Biosystems’ BigDye Terminator 3.1 Cycle Sequencing Kit, and sequencing was conducted on an Applied Biosystems 3130xl Genetic Analyzer. The chromatogram data was analyzed using FinchTV 1.5.0 (Geospiza Inc., USA). Table S1 (See Supplementary Online Information at www.ijfs.ir) shows primers properties. Table 1. Sperm analysis Subject II-4 II-6 Age (Y) 46 39 History of infertility (Y) 18 13 Sperm count concentration (20×10 6 sperm/ml) 93 84 Sperm motility (≥40% motile) 60.6 71 Sperm morphology Normal Normal (head and neck) IVF attempted 2 - Open in a new tab IL; Interleukin and IVF; In vitro fertilization. In silico prediction of structural-functional consequences using MutPred2, Project HOPE and mCSM Three bioinformatics web servers were used to evaluate the disease-causing potential and molecular effects of candidate variants on protein function. MutPred2 (http://mutpred.mutdb.org) is a machine-learning tool that predicts each variant’s MutPred2 score and probability score (p-score) using genetic and molecular data ( 23 ). Also, Project Have Our Protein Explained (HOPE) (https://www3.cmbi.umcn.nl/hope) was recruited. This automated analysis server evaluates the physicochemical properties of wild-type and mutant residues, as well as the impact of mutant residues on protein threedimensional structure ( 24 ). Additionally, we utilized mCSM, (https://biosig.lab.uq.edu.au/mcsm/) to encode atom distances using graph-based signatures. These signatures reflect protein residue environments and train predictive models to understand mutation impacts on disease. Mutations are considered for protein stability, protein-protein, and protein-nucleic acid interactions ( 25 ). To demonstrate the effects of the variants at the molecular level, we provided the DNAH5 sequence in FASTA format (accession number: Q8TE73 .DYH5_HUMAN in the UniProt database) together with variation data as the input query. DNAH5 3D structure visualization The Protein Data Bank (PDB) (https://www.rcsb.org/) was used to obtain the 3D structure of DNAH5 for structural analysis. The DNAH5 protein structure was found in the human respiratory doublet microtubule and associated axonemal complexes (PDB Accession ID: 8J07). The 3D complex structure was determined using electron microscopy at a resolution of 4.1 A˚. We used VMD 1.9.3 to visualize the complex structure, retrieved the DNAH5 and additional protein chains 5 A˚ of DNAH5. Then, VMD was used to measure the distances between two mutated amino acids and adjacent amino acids in the other protein chains, as well as ATP-binding sites. Results Compound heterozygous missense variants in the DNAH5 gene were identified using whole-exome se quencing Whole Exome Sequencing was carried out on the genomic DNA samples obtained from the proband (II-4). The quality filter was met by approximately 93% of total reads (Q ≥30). Data filtering was conducted using a threshold of MAF<0.01, and male infertility panels were applied. It was hypothesized that the inheritance pattern within the family could be autosomal recessive; however, no candidate variants were identified to support this hypothesis. Due to the absence of genetic relatedness between the parents, an autosomal dominant inheritance pattern was suspected. Following the exclusion of intronic, intergenic, and synonymous single nucleotide variants (SNVs), no candidate variant consistent with this inheritance model and male infertility was identified—except for two missense variants in a compound heterozygous (CH) pattern in the DNAH5 gene. The first variant with MAF=0.000751 (chr5:13916533- A>G; c.1121T>C; p. I374T) is located in exon 9 of the DNAH5 gene ( NM_001369.3 ), while the second variant with MAF=0.00122 (Chr5:13737379-G>A; c.11437C>T; p. R3813W) is located in exon 66 of this gene ( Fig .2A ). The mutations (c.1121T>C; p. I374T) and (c.11437C>T; p. R3813W) have the potential to cause disease, as indicated by the Mutation taster, SIFT, and Polyphen-2 software. However, these mutations are classified as variants of uncertain significance (VUS) in the Franklin and InterVar databases. DANN and FATHMM_MKL classified them as VUS. Therefore, MobiDetails predicted one variant (c.11437C>T; p. R3813W) as damaging, while the other variant (c.1121T>C; p. I374T) was classified as UVS. ClinVar classified both variants as having conflicting interpretations. Multiple sequence alignment to assess the conservation of the variant (c.11437C>T; p. R3813W) shows a high level of conservation among mammals, while the other variant (c.1121T>C; p. I374T) is conserved to a level that raises concern ( Fig .2B ). In terms of pathogenicity categorization, the variants were categorized as VUS based on the standards provided by the American College of Medical Genetics and Genomics (ACMG) ( 26 ). Fig.2. Open in a new tab Identification of compound heterozygotes missense DNAH5 variant in a family lead to infertility. A. DNAH5 is located on chromosome 5p15.2 and composed of 79 exons encoding the 4624-amino acid protein. The uncovered variant (c.1121T>C; p. I374T) affects exon 9 and (c.11437C>T; p. R3813W) affects exon 66. variant (c.1121T>C; p. I374T) is located in DHC-N1 domains while (c.11437C>T; p. R3813W) variant placed between two AAA domain near the AAA-5. B. Multiple sequence alignment indicates that the amino acid residues are highly conserved among mammals. Compound heterozygote variants segregated in the family were confirmed Compound heterozygote variants were verified in two affected patients (II-4, III-6) through Sanger sequencing. The Sanger sequencing of the DNAH5 variants determined the variants were trans-presentation in the proband and his infertile brother (II-4, III-6). The variation (Chr5:13916533 A>G; c.1121T>C; p. I374T) was inherited paternally, while the variant (Chr5:13737379 G>A; c.11437C>T; p. R3813W) was inherited maternally. The control, fertile brother (II-7), inherited the same genetic traits as the father (I-1) ( Fig .3 ). Fig.3. Open in a new tab Sanger verification and segregation analysis in a recruited family. HOM; Homozygous and HET; Heterozygous. DNAH5 missense variants may impact on the on protein structure due to in silico prediction sits The mutations c.1121T>C and c.11437C>T are located at base positions 13916533 and 13737379 in the p15.2 region of chromosome 5, respectively ( Fig .2A ). These mutations result in substituting the positions 374 isoleucine subunit of the DNAH5 protein with a threonine subunit and 3813 arginine subunit with a tryptophan subunit. These variants are highly conserved across different mammals ( Fig .2B ). Furthermore, the Mutationtaster software suggests that these mutations may lead to the development of a disease. The DNAH5 protein is composed of 4624 amino acid subunits. The DNAH5 protein consists of two DHC-N domains, six AAA domains, a coiled-coil stalk domain, and a Dynein Heavy domain ( Fig .2A ). The variant c.1121T>C (p. I374T) affects exon 9 and is situated in the DHC-N1 domains, while the variant c.11437C>T (p. R3813W) affects exon 66 and is positioned between two AAA domains near the AAA-5 ( Fig .2A ). The MutPred2 server was used to analyze the impact of the variations p. I374T and p. R3813W in the DNAH5 gene on the structure, function, and pathogenicity of the protein. The server assigned g-scores of 0.561 and 0.889 to these substitutions, respectively, as shown in Table S2 Table S2 (See Supplementary Online Information at www.ijfs.ir). According to the MutPred2 analysis, these variations are likely to be diseasecausing. The analysis identified two molecular mechanisms that were modified: a changed coiled-coil structure and the gain of an allosteric site at Y3816. These modifications were associated with P=0.0093 and 0.0035, respectively, indicating a high confidence level in the observed changes. By integrating the g-scores and P values, we can gain insights into the potential impact of these mutations on disease (Table S2, See Supplementary Online Information at www.ijfs. ir). Therefore, the findings from MutPred2 support the idea that these variants might significantly affect the structural and functional properties of the DNAH5 protein. The data collected from project hope regarding the DNAH5 protein is divided into two distinct categories. Due to limited server capacity, HOPE could not process very long sequenc es. We identified the domain of interest from the NCBI database, which spans residues 250 to 802 for I374T, and used this sequence for a HOPE request. Additionally, we supplied a 700-amino-acid segment that surrounds the R3813W mutation. Concerning the impact of potential variants on the structure of the protein, project hope has projected that the wild-type residue is situated in position. As a result, the local conformation of the protein could be slightly destabilized. HOPE did not predict the 3D structure for DNAH5 since there was not enough sequence available. However, it identified differences in physicochemical parameters, including size and hydrophobicity, between the wild-type and mutant forms ( Table S3 , See Supplementary Online Information at www.ijfs.ir). The data from HOPE corresponding to I374T shows that the mutant amino acid is smaller and has different hydrophobic properties compared to the wild-type. This discrepancy could potentially disrupt molecular contacts and hydrogen bonds. The altered residue is located within a critical domain responsible for binding other molecules, specifically within an amino acid segment recognized by UniProt as a distinct region called "Stem." Changes in amino acid characteristics in this area may impair its function. The mutation of arginine to tryptophan at position 3813 results in a larger mutant residue compared to the wild-type residue. Additionally, this mutation causes the loss of the charge associated with the wild-type residue. The charge of the wild-type residue was positive, while the charge of the mutant residue was neutral. The residue is situated on the protein's surface, and altering this residue can disrupt interactions with other molecules or other regions of the protein. The mutant residue exhibits a higher degree of hydrophobicity compared to the wild-type residue. The mutation could potentially affect this interaction, resulting in a disruption of signal transmission from the binding domain to the activity domain. The difference in charge could interrupt the ionic connection formed by the original wild-type residue. mCSM is a tool used to analyze the effects of missense mutations on proteins. It utilizes graph-based signatures to analyze the alteration in Gibbs free energy (ΔG) and the influence of mutations on protein stability. The task involves predicting both the numerical value and the direction of change in ΔG, as well as the relative accessible surface area (RSA) of a protein residue, which measures the residue’s solvent exposure. The two variants predicted may cause destabilization in DNAH5 protein. The presence of mutations I374T (with a ΔΔG of-1.912 and 29.3% RSA) and R3813W (with a ΔΔG of-0.472 and 46.7% RSA) in the protein suggests that it is unlikely to be in a stable state. Structural analysis of DNAH5 revealed the impact of mutations on its function The DNAH5 structure in the human respiratory doublet microtubule and associated axonemal complexes was found from the PDB with accession ID 8J07 ( Fig .4A ). The structure of DNAH5 was visualized to assess the impact of specific mutations on its structure and function. DNAH5 structure was retrieved alongside other protein chains within 5 A˚ ( Fig .4B ). The ODA consists of a head with six ATPase domains for ATP hydrolysis and a tail that maintains complex integrity. The motor tethering domain (MTD) A-tubule is permanently linked to the tail, while the head component contains a microtubulebinding domain (MTBD) that interacts with the MTD B-tubule based on nucleotide states. Neighboring OADs are connected through linker structures. Therefore, a trimeric ODA-docking complex is responsible for binding the ODA to the microtubules ( 27 ). It has been concluded that ODA Docking Subunit 1 (ODA-D1/CCDC114) interacts directly with ODA Docking Subunit 3 (ODA-D3/ CCDC151), with mutual interactions likely occurring through their coiled-coil domains. This interaction helps position the ODA at its binding site on the doublet microtubule ( 27 , 28 ). Mutations in DNAH5 (c.1121T>C; p.Ile374Thr and c.11437C>T; p.Arg3813Trp) were introduced at distinct protein sites ( Fig .4B ). The variant I374T is located near ODA-D1 and ODA-D3, with a distance of less than 10 A˚ ( Fig .4C ). The ATP-binding domain which contains residues of 3575 to 3795 is located near the R3813W mutation ( Fig .4D ). The R3813W mutation was found within 4 A˚ of residues 3732 and 3728 in the ATP-binding domain (positions 3575-3795). These structural results highlight the effect of the I374T mutation on the interaction of DNAH5 with ODA-D1 and ODA-D3, as well as the impact of the R3813W mutation on the ATP-binding domain. Fig.4. Open in a new tab Representation of the three-dimensional (3D) structure of DNAH5. A. The respiratory doublet microtubule and associated axonemal complexes. B. The DNAH5 structure in complex with Outer Dynein Arm-Docking Subunit 1 (ODA-D1) and ODA-D3 is shown. The Ile374Thr and Arg3813Trp mutations are colored red and magenta, respectively. C. The residues 304, 305, 308, 309, 312, and 315 in ODA-D1 (green), and residues 391 and 395 in ODA-D3 (orang) are near the Ile374Thr mutation (less than 10 A˚). D. The R3813W (magenta) mutation is located near the ATP-binding dynein motor region (3575-3795) (dark blue). The 3732 and 3728 residues of the ATP binding site are within 4 A˚ of R3813W. Discussion DNAH5 encodes dynein proteins that play a crucial role in the development of external axon dynein arms in cilia and flagella ( 29 ). Given the strong conservation of DNAH5 and other dynein proteins, such as DNAH11, across various species, it is reasonable to expect that mutations in these proteins could significantly affect sperm motility ( 10 , 30 ). The ODA complexes are attached to the outer circumference of microtubules and consist of three heavy chains, two intermediate chains, and eleven light chains ( 31 ). DNAH5, one of the three major heavy chains, has 79 exons and is essential for the proper movement of microtubules and cilia ( 10 ). Dynein is a motor protein associated with ciliary microtubules, aiding in their movement and in the transport of molecules. It utilizes adenosine triphosphate (ATP) to move toward the minus end of microtubules and is also involved in the initial stages of mammalian mitotic spindle formation ( 32 ), viral replication ( 33 ), and eukaryotic cilium activity ( 27 - 29 ). The ODA complexes consist of two distinct types: type 1 (comprised of DNAH11 and DNAH5, located in the proximal section of the axoneme) and type 2 (comprising DNAH9 and DNAH5, positioned distally to the axoneme) ( 34 , 35 ). While the exact connection between the DNAH5 and DNAH11 genes and male infertility remains unclear, it is established that these genes play crucial roles in the flagellar external axonemal power arm. Mutations in the DNAH5 or DNAH11 genes have been associated with decreased sperm motility. Previous studies indicate that 90% of individuals with Kartagener syndrome or PCD, along with asthenozoospermia, carry genetic anomalies in dynein genes, including DNAH11, CCDC40, DNAI1, and DNAH5 ( 30 , 36 ). Pereira and his colleagues demonstrated that mutations in the DNAH5 gene result in reduced sperm motility. They found that individuals with primary spermatogenic failure had two deleterious DNAH5 mutations, specifically rs748618094 and p.Lys1853 * ( 37 ). In their study, Heidary et al. ( 30 ) discovered two specific mutations in the DNAH5 gene, observed in 7.5% of males diagnosed with asthenozoospermia. Truncating mutations in the DNAH5 gene cause aberrant structural and motor activity of the sperm's cilia, leading to the absence of the external dynein arm ( 10 ). Most studies suggest that dynein genes are involved in syndromic asthenozoospermia ( 34 , 38 ). However, Zuccarello et al. ( 9 ) found that their association with non-syndromic asthenozoospermia occurs in only 1.1% of cases. In their research, the authors found that individuals with heterozygous mutations in the DNAH5, DNAH11, and other related genes displayed idiopathic asthenozoospermia but did not exhibit any clinical symptoms of PCD. This suggests that asthenozoospermia might be considered a milder form of PCD syndrome. Furthermore, studies have indicated that genetic abnormalities in the DNAH5 gene can lead to infertility issues, such as azoospermia or oligozoospermia ( 9 , 29 , 34 ). The condition known as teratoasthenozoospermia is characterized by reduced sperm motility and normal sperm morphology, which has been linked to decreased expression of DNAH5. The gene linc02220 may serve as a regulatory target for DNAH5 , potentially impacting the normal movement and shape of sperm. Abnormalities in sperm motility or morphology may arise from mutations in their coding sequences ( 39 ). In a comprehensive investigation conducted in 2022, researchers found that mutations in DNAH5 lead to impaired ciliary function and a weakened immune response. This conclusion was drawn from single-cell RNA sequencing (scRNA-Seq) and proteome studies. Furthermore, the deliberate stimulation of ciliated cells through TGF-β/BMP and the Notch pathway resulted in increased expression of inflammatory cytokines ( 40 ). Overall, DNAH5 consists of various components. Its N-terminal domain interacts with intermediate and light chains, while its motor domain, referred to as the core, includes a heptameric AAA subdomain with ATPase activity, a connecting stalk, and a microtubule-binding domain ( 27 , 28 ). Mutation p.I374T occurs in the stem region of the DHC-N1 domain, while mutation p.R3813W is found in a unique 15-amino-acid region located 4 Å from the ATP-binding site of the dynein motor. Changing the hydropho bic Ile residue to the polar, uncharged Thr residue in 374 can affect the interaction of DNAH5 with ODA-D1 and ODA-D3. Conversely, replacing the positively charged Arg residue with a hydrophobic Trp residue in 3813 impacts ATP binding. Although no effects on the sperm parameters of patients have been detected, they may influence mitotic spindle formation ( 32 ), signaling pathways ( 40 ), and the proper functioning of the DNAH5 protein. This could potentially contribute to male infertility. This study has identified potentially pathogenic CH variants in the DNAH5 gene. However, like any research, it has its limitations. One major challenge was the difficulty in recruiting a larger sample size, specifically more infertile men with unexplained causes despite having normal semen parameters. Additionally, not all family members participated in the study, which further limited the findings. Conclusion This study identified two compound heterozygous missense variants in the DNAH5 gene—c.1121T>C (p.I374T) and c.11437C>T (p.R3813W)—in two infertile siblings, using whole exome and Sanger sequencing. While both variants are currently classified as VUS, multiple in silico prediction tools suggest potential pathogenicity, particularly due to their high evolutionary conservation and predicted structural and functional impact on the DNAH5 protein. Structural modeling and stability analyses indicate that these variants may disrupt protein conformation and critical domain interactions, including ATP-binding and dynein arm assembly, both vital for proper ciliary and flagellar function. Although a definitive clinical link to infertility requires further validation, the findings contribute to the growing evidence that DNAH5 mutations may underlie certain forms of non-syndromic PCD, supporting the gene’s broader role in male reproductive health. Supplementary PDF Int-J-Fertil-Steril-20-2-159-s01.pdf (400.8KB, pdf) Acknowledgments We sincerely thank the personnel of the Genetics Department at the Royan Institute for Reproductive Biomedicine. We extend our sincere appreciation to the participants and their loved ones for their active involvement in this study. This work is based upon research funded by Iran National Science Foundation (INSF) under project No. 4012868 and Lotus Charity Found under project No. D/1402/4341. Author’s Contributions. M.A.; Collected clinical information and samples, Analyzed the WES data, Validated the WES results by Sanger sequencing, Conceptualization, Performed structure analysis, Visualization, and Writing-original draft preparation. N.S.; Performed protein structure analysis, Reviewed, and Edited. H.-D.S.; Clinically examined the patients’ tests. M.S.; Reviewed and Edited. S.A.Sh.-F., A.A.-Y. Designed and supervised the study, Provided the funding, Reviewed, and Edited. All Authors read and approved the final manuscript. Footnotes Conflict of Interest: Marjan Sabbaghian, Seyed Abolhassan Shahzadeh-Fazeli, and Amir Amiri-Yekta are is a reviewer for this journal, they did not participate in the peer review process for this manuscript, and the review has been handled independently by other editors/reviewers. References 1. Eisenberg ML, Esteves SC, Lamb DJ, Hotaling JM, Giwercman A, Hwang K, et al. Male infertility. Nat Rev Dis Primers. 2023;9(1):49–49. doi: 10.1038/s41572-023-00459-w. doi: 101038/s41572-023-00459-w. [ DOI ] [ PubMed ] [ Google Scholar ] 2. Moraes AP, Barreto SM, Passos VM, Golino PS, Costa JA, Vascon celos MX. Incidence and main causes of severe maternal morbidity in São Luís, Maranhão, Brazil: a longitudinal study. Sao Paulo Med J. 2011;129(3):146–152. doi: 10.1590/S1516-31802011000300005. doi: 101590/s1516-31802011000300005. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 3. Tournaye H, Krausz C, Oates RD. Novel concepts in the aetiol ogy of male reproductive impairment. Lancet Diabetes Endocrinol. 2017;5(7):544–553. doi: 10.1016/S2213-8587(16)30040-7. doi: 101016/S2213-8587(16)30040-7. [ DOI ] [ PubMed ] [ Google Scholar ] 4. Pandruvada S, Royfman R, Shah TA, Sindhwani P, Dupree JM, Schon S, et al. Lack of trusted diagnostic tools for undetermined male infertility. J Assist Reprod Genet. 2021;38(2):265–276. doi: 10.1007/s10815-020-02037-5. doi: 101007/s10815-020-02037-5. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 5. Fliegauf M, Benzing T, Omran H. When cilia go bad: cilia defects and ciliopathies. Nat Rev Mol Cell Biol. 2007;8(11):880–893. doi: 10.1038/nrm2278. doi: 101038/nrm2278. [ DOI ] [ PubMed ] [ Google Scholar ] 6. Satir P, Mitchell DR, Jékely G. How did the cilium evolve? Curr Top Dev Biol. 2008;85:63–82. doi: 10.1016/S0070-2153(08)00803-X. doi: 101016/S0070-2153(08)00803-X. [ DOI ] [ PubMed ] [ Google Scholar ] 7. Dong FN, Amiri-Yekta A, Martinez G, Saut A, Tek J, Stouvenel L, et al. Absence of CFAP69 causes male infertility due to multiple mor phological abnormalities of the flagella in human and mouse. Am J Hum Genet. 2018;102(4):636–648. doi: 10.1016/j.ajhg.2018.03.007. doi: 101016/jajhg201803007. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 8. Coutton C, Vargas AS, Amiri-Yekta A, Kherraf ZE, Ben Mustapha SF, Le Tanno P, et al. Mutations in CFAP43 and CFAP44 cause male infertility and flagellum defects in Trypanosoma and human. Nat Commun. 2018;9(1):686–686. doi: 10.1038/s41467-017-02792-7. doi: 101038/s41467-017-02792-7. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 9. Zuccarello D, Ferlin A, Cazzadore C, Pepe A, Garolla A, Moretti A, et al. Mutations in dynein genes in patients affected by isolated non-syndromic asthenozoospermia. Hum Reprod. 2008;23(8):1957–1962. doi: 10.1093/humrep/den193. doi: 101093/humrep/den193. [ DOI ] [ PubMed ] [ Google Scholar ] 10. Hornef N, Olbrich H, Horvath J, Zariwala MA, Fliegauf M, Loges NT, et al. DNAH5 mutations are a common cause of primary ciliary dyskinesia with outer dynein arm defects. Am J Respir Crit Care Med. 2006;174(2):120–126. doi: 10.1164/rccm.200601-084OC. doi: 101164/rccm200601-084OC. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 11. Miller SA, Dykes DD, Polesky HF. A simple salting out procedure for extracting DNA from human nucleated cells. Nucleic Acids Res. 1988;16(3):1215–1215. doi: 10.1093/nar/16.3.1215. doi: 101093/nar/1631215. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 12. Andrews S. FastQC.a quality control tool for high throughput sequence data.Cambridge.United Kingdom. United Kingdom; 2010. Avialable from: https://www.bioinformatics.babraham.ac.uk/projects/fastqc . [ Google Scholar ] 13. Li H, Durbin R. Fast and accurate short read alignment with Bur rows-Wheeler transform. Bioinformatics. 2009;25(14):1754–1760. doi: 10.1093/bioinformatics/btp324. doi: 101093/bioinformatics/btp324. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 14. McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kerny tsky A, et al. The Genome Analysis Toolkit: a MapReduce frame work for analyzing next-generation DNA sequencing data. Genome Res. 2010;20(9):1297–1303. doi: 10.1101/gr.107524.110. doi: 101101/gr107524110. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 15. DePristo MA, Banks E, Poplin R, Garimella KV, Maguire JR, Hartl C, et al. A framework for variation discovery and genotyping us ing next-generation DNA sequencing data. Nat Genet. 2011;43(5):491–498. doi: 10.1038/ng.806. doi: 101038/ng806. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 16. Wang Y, Stojiljković N, Jehle JA. Cloning of complete genomes of large dsDNA viruses by in vitro transposition of an F factor contain ing transposon. J Virol Methods. 2010;167(1):95–99. doi: 10.1016/j.jviromet.2009.11.026. doi: 101016/jjviromet200911026. [ DOI ] [ PubMed ] [ Google Scholar ] 17. Sherry ST, Ward MH, Kholodov M, Baker J, Phan L, Smigielski EM, et al. dbSNP: the NCBI database of genetic variation. Nucleic Acids Res. 2001;29(1):308–311. doi: 10.1093/nar/29.1.308. doi: 101093/nar/291308. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 18. 1000 Genomes Project Consortium. Abecasis GR, Auton A, Brooks LD, DePristo MA, Durbin RM, et al.An integrated map of genetic variation from 1,092 human genomes. Nature. 2012;491(7422):56–65. doi: 10.1038/nature11632. doi: 101038/nature11632. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 19. Tennessen JA, Bigham AW, O'Connor TD, Fu W, Kenny EE, Grav el S, et al. Evolution and functional impact of rare coding varia tion from deep sequencing of human exomes. Science. 2012;337(6090):64–69. doi: 10.1126/science.1219240. doi: 101126/science1219240. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 20. Karczewski KJ, Francioli LC, Tiao G, Cummings BB, Alföldi J, Wang Q, et al. The mutational constraint spectrum quantified from variation in 141,456 humans. Nature. 2020;581(7809):434–443. doi: 10.1038/s41586-020-2308-7. doi: 101038/s41586-020-2308-7. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 21. Lek M, Karczewski KJ, Minikel EV, Samocha KE, Banks E, Fennell T, et al. Analysis of protein-coding genetic variation in 60,706 hu mans. Nature. 2016;536(7616):285–291. doi: 10.1038/nature19057. doi: 101038/nature19057. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 22. Chun S, Fay JC. Identification of deleterious mutations within three human genomes. Genome Res. 2009;19(9):1553–1561. doi: 10.1101/gr.092619.109. doi: 101101/gr092619109. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 23. Pejaver V, Urresti J, Lugo-Martinez J, Pagel KA, Lin GN, Nam HJ, et al. Inferring the molecular and phenotypic impact of amino acid variants with MutPred2. Nat Commun. 2020;11(1):5918–5918. doi: 10.1038/s41467-020-19669-x. doi: 101038/s41467-020-19669-x. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 24. Venselaar H, Te Beek TA, Kuipers RK, Hekkelman ML, Vriend G. Protein structure analysis of mutations causing inheritable dis eases.An e-Science approach with life scientist friendly interfaces. BMC Bioinformatics. 2010;11:548–548. doi: 10.1186/1471-2105-11-548. doi: 101186/1471-2105-11-548. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 25. Pires DE, Ascher DB, Blundell TL. mCSM: predicting the effects of mutations in proteins using graph-based signatures. Bioinformat ics. 2014;30(3):335–342. doi: 10.1093/bioinformatics/btt691. doi: 101093/bioinformatics/btt691. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 26. Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, et al. Standards and guidelines for the interpretation of sequence vari ants: a joint consensus recommendation of the American College of medical genetics and genomics and the association for mo lecular pathology. Genet Med. 2015;17(5):405–424. doi: 10.1038/gim.2015.30. doi: 101038/ gim201530. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 27. Rao Q, Han L, Wang Y, Chai P, Kuo YW, Yang R, et al. Structures of outer-arm dynein array on microtubule doublet reveal a motor coordination mechanism. Nat Struct Mol Biol. 2021;28(10):799810–799810. doi: 10.1038/s41594-021-00656-9. doi: 101038/s41594-021-00656-9. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 28. Walton T, Gui M, Velkova S, Fassad MR, Hirst RA, Haarman E, et al. Axonemal structures reveal mechanoregulatory and disease mechanisms. Nature. 2023;618(7965):625–633. doi: 10.1038/s41586-023-06140-2. doi: 101038/ s41586-023-06140-2. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 29. Aprea I, Nöthe-Menchen T, Dougherty GW, Raidt J, Loges NT, Kai ser T, et al. Motility of efferent duct cilia aids passage of sperm cells through the male reproductive system. Mol Hum Reprod. 2021;27(3):gaab009–gaab009. doi: 10.1093/molehr/gaab009. doi: 101093/molehr/gaab009. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 30. Heidary Z, Saliminejad K, Zaki-Dizaji M, Khorram Khorshid HR. Genetic aspects of idiopathic asthenozoospermia as a cause of male infertility. Hum Fertil (Camb) 2020;23(2):83–92. doi: 10.1080/14647273.2018.1504325. doi: 101080/1464727320181504325. [ DOI ] [ PubMed ] [ Google Scholar ] 31. Oda T, Abe T, Yanagisawa H, Kikkawa M. Structure and function of outer dynein arm intermediate and light chain complex. Mol Biol Cell. 2016;27(7):1051–1059. doi: 10.1091/mbc.E15-10-0723. doi: 101091/mbcE15-10-0723. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 32. Vaisberg EA, Koonce MP, McIntosh JR. Cytoplasmic dynein plays a role in mammalian mitotic spindle formation. J Cell Biol. 1993;123(4):849–858. doi: 10.1083/jcb.123.4.849. doi: 101083/jcb1234849. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 33. Dodding MP, Way M. Coupling viruses to dynein and kinesin-1. EMBO J. 2011;30(17):3527–3239. doi: 10.1038/emboj.2011.283. doi: 101038/emboj2011283. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 34. Fliegauf M, Olbrich H, Horvath J, Wildhaber JH, Zariwala MA, Kenne dy M, et al. Mislocalization of DNAH5 and DNAH9 in respiratory cells from patients with primary ciliary dyskinesia. Am J Respir Crit Care Med. 2005;171(12):1343–1349. doi: 10.1164/rccm.200411-1583OC. doi: 101164/rccm200411-1583OC. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 35. Loges NT, Antony D, Maver A, Deardorff MA, Güleç EY, Gezdirici A, et al. Recessive DNAH9 loss-of-function mutations cause laterality defects and subtle respiratory ciliary-beating defects. Am J Hum Genet. 2018;103(6):995–1008. doi: 10.1016/j.ajhg.2018.10.020. doi: 101016/jajhg201810020. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 36. Storm van's Gravesande K, Omran H. Primary ciliary dyskinesia: clinical presentation, diagnosis and genetics. Ann Med. 2005;37(6):439–449. doi: 10.1080/07853890510011985. doi: 101080/07853890510011985. [ DOI ] [ PubMed ] [ Google Scholar ] 37. Pereira R, Oliveira J, Ferraz L, Barros A, Santos R, Sousa M. Muta 168 tion analysis in patients with total sperm immotility. J Assist Reprod Genet. 2015;32(6):893–902. doi: 10.1007/s10815-015-0474-6. doi: 101007/s10815-015-0474-6. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 38. Sironen A, Shoemark A, Patel M, Loebinger MR, Mitchison HM. Sperm defects in primary ciliary dyskinesia and related causes of male infertility. Cell Mol Life Sci. 2020;77(11):2029–2048. doi: 10.1007/s00018-019-03389-7. doi: 101007/s00018-019-03389-7. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 39. Kamel A, Saberiyan M, Adelian S, Teimori H. DNAH5 gene and its correlation with linc02220 expression and sperm characteristics. Mol Biol Rep. 2022;49(10):9365–9372. doi: 10.1007/s11033-022-07787-2. doi: 101007/s11033-022-07787-2. [ DOI ] [ PubMed ] [ Google Scholar ] 40. Yang W, Chen L, Guo J, Shi F, Yang Q, Xie L, et al. Multiomics analysis of a DNAH5-mutated PCD organoid model revealed the key role of the TGF-β/BMP and notch pathways in epithelial dif ferentiation and the immune response in DNAH5-mutated patients. Cells. 2022;11(24):4013–4013. doi: 10.3390/cells11244013. doi: 103390/cells11244013. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Associated Data This section collects any data citations, data availability statements, or supplementary materials included in this article. Supplementary Materials Int-J-Fertil-Steril-20-2-159-s01.pdf (400.8KB, pdf) Articles from International Journal of Fertility & Sterility are provided here courtesy of Royan Institute ACTIONS View on publisher site PDF (4.4 MB) Cite Collections Permalink PERMALINK Copy RESOURCES Similar articles Cited by other articles Links to NCBI Databases Cite Copy Download .nbib .nbib Format: AMA APA MLA NLM Add to Collections Create a new collection Add to an existing collection Name your collection * Choose a collection Unable to load your collection due to an error Please try again Add Cancel Follow NCBI NCBI on X (formerly known as Twitter) NCBI on Facebook NCBI on LinkedIn NCBI on GitHub NCBI RSS feed Connect with NLM NLM on X (formerly known as Twitter) NLM on Facebook NLM on YouTube National Library of Medicine 8600 Rockville Pike Bethesda, MD 20894 Web Policies FOIA HHS Vulnerability Disclosure Help Accessibility Careers NLM NIH HHS USA.gov Back to Top