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. 2019 Dec 4;36(12):2563–2573. doi: 10.1007/s10815-019-01614-7

Association of UHRF1 gene polymorphisms with oligospermia in Chinese males

Weiqiang Zhu 1,2, Jing Du 2, Qing Chen 1, Zhaofeng Zhang 2, Bin Wu 2, Jianhua Xu 2, Tianqi Li 2, Yuan Bi 2, Huijuan Shi 2,✉, Runsheng Li 2,✉
PMCID: PMC6911149  PMID: 31802345

Abstract

Background

UHRF1 plays an important role in maintaining DNA methylation patterns during spermatogenesis. This study was performed to evaluate the association between UHRF1 gene variations and infertility in males with oligozoospermia in a Chinese population.

Methods

In this case-control study of 735 Chinese men, single-nucleotide polymorphism (SNP) genotypes and alleles in the UHRF1 gene were assessed by direct sequencing. The effects of the mutations on UHRF1 transcription were investigated using a dual-luciferase reporter gene assay.

Results

We identified 24 SNPs, including nine SNPs in the promoter region, three in the 5′ untranslated region, five in introns, and seven in exons. Interestingly, the genotype frequencies of SNP rs2656927 (P = 0.014) and rs8103849 (P < 0.001) significantly differed between men with oligozoospermia in case group 1 and normozoospermic men. Moreover, four variants (three were novel) were detected only in the patient group, with two in introns and the others in the promoter region. The results of the luciferase assay showed that the -1615C>T-C and -1562A>G-A alleles increased luciferase activity compared with the -1615C>T-T and -1562A>G-G alleles.

Conclusions

We detected two SNPs in the UHRF1 gene showing a significant difference between the case and control groups. Two screened SNPs affected UHRF1 promoter activity, improving the understanding of the pathophysiology of oligozoospermia.

Electronic supplementary material

The online version of this article (10.1007/s10815-019-01614-7) contains supplementary material, which is available to authorized users.

Keywords: UHRF1, Polymorphism, Promoter, Oligozoospermia

Introduction

Infertility affects approximately 15% of couples worldwide [1]. Numerous genes have been suggested to be potentially associated with male infertility [2–4]. However, these genes can only explain a small proportion of male infertility, and the pathophysiology is not well-understood. Determining the exact etiology and pathophysiology of infertility remains a critical challenge. Infertility is thought to be related to epigenetic factors such as sperm DNA methylation, chromatin remodeling, histone modifications, and RNAs, which may deteriorate spermatogenesis either alone or in combination with environmental factors [5].

As the most widely studied type of epigenetic modification, DNA methylation exhibits dynamic changes during spermatogonial stem cell (SSC) formation and differentiation [6] and is thought to play a fundamental role in male germline development [7]. DNA methylation in the male germline plays an important role in preventing retrotransposons from participating in meiotic recombination [8], and in regulating the expression of germ cell-specific genes [9]. Altered DNA methylation has been widely identified in the spermatozoa of infertile men [10, 11]. For instance, the paternally expressed human gene MEST is demethylated in the fetus and remains unmethylated throughout sperm development in human spermatogenesis [12]. In contrast, in male germ cells, the H19 gene is methylated prior to meiosis at the spermatogonial stage of development [12]. Both H19 hypomethylation and MEST hypermethylation have been detected in the sperm of infertile men [13]. However, the origins of these errors are poorly understood.

Genetic variations in DNA-methylation-regulating genes including DNA methyltransferase I (DNMT1) have been found to be associated with male infertility [14–17]. DNMT1, the most abundant DNMT in mammalian cells, is considered as the key maintenance methyltransferase during cell division [18, 19]. Knockout of DNMT1 in mouse embryonic stem cells resulted in a lack of DNA methylation, preventing genomic imprinting which was followed by apoptosis of spermatogonial cells [20, 21]. DNMT1 predominantly methylates hemimethylated CpG dinucleotides in the genome. The hemimethylated-CG-binding protein UHRF1 (ubiquitin-like-containing plant homeodomain and ring finger 1) plays a critical role in maintaining CG methylation by recruiting DNMT1 to hemimethylated CG sites [22].

UHRF1 is a multi-domain nuclear protein, containing a ubiquitin-like domain, Tudor domain, plant homeodomain, SET domain, and RING-associated domain and RING finger domain. It is mostly expressed in proliferating cells, whereas it is not found in fully differentiated tissues [23]. Many studies have validated UHRF1 as a powerful diagnostic and prognostic tool for differentially diagnosing cancer and predicting therapeutic responses and for assessing the risk of tumor progression and recurrence [24]. The oncogenic role of UHRF1 is largely associated with DNA hypermethylation in the promoters of tumor suppressor genes [25–27].

Additionally, UHRF1 is highly expressed in mouse testis tissues [28], not only in proliferating spermatogonia but also in meiotic spermatocytes and differentiating spermatids that are not proliferating [29]. A mechanism study showed that ablation of UHRF1 interfered with differentiation and viability only after spermatogonia became Kit-positive (a marker of differentiating spermatogonia) [30]. However, whether mutations in UHRF1 are related to male infertility is unclear. The association of polymorphisms in UHRF1 and human diseases has not been reported. In the current study, we aimed to identify single-nucleotide polymorphisms (SNPs) in UHRF1 and evaluate their effects in 393 idiopathic male infertility cases and 342 normal controls to explore the association between UHRF1 and the pathophysiology of oligozoospermia.

Material and methods

Study samples

This study was approved by the Ethics Committee of Shanghai Institute of Planned Parenthood Research (SIPPR) on Human Research. All participants were of Han Chinese ancestry and lived in the Shanghai area. And all participants were collected with a written informed consent form in accordance with the Declaration of Helsinki.

  1. Case group: A total of 393 infertile patients with oligozoospermia (semen count less than 20 × 106/mL), and mean age 31.95 ± 3.21, were recruited from the Shanghai Institute of Planned Parenthood Research Hospital. All patients undertook World Health Organization (WHO) standard semen analysis at least twice and were excluded from diseases such as urinary tract infection, spermaduct obstruction, testicular tumors or orchitis, and no Y chromosome microdeletion. Two groups of infertile patients were generated according to their sperm density: case group 1 (289 idiopathic infertile men with sperm concentration < 15 × 106/mL) and case group 2 (104 idiopathic infertile men with sperm concentration 15–20 × 106/mL).

  2. Control group: 342 normozoospermia without any history of primary or secondary infertility and with semen count more than 20 × 106/mL, and mean age 32.16 ± 3.26, were randomly enrolled from the same hospital in this case-control study. All controls were healthy men with normal reproductive function and confirmed to have healthy babies 6–8 months later.

Semen assessments

Each male donated 1 mL (case cohort) or 0.5 mL (control cohort) of semen that was obtained by masturbation after at least 4 days of abstinence; this abstinence period was based on the standard protocol used in the collaborating infertility clinic. Each ejaculate was subjected to a classical seminal analysis approximately 30 min after liquefaction based on the recommendations and semen evaluation protocols and standards of the World Health Organization (2010); parameters analyzed included sperm concentration and sperm motility.

Isolation of DNA, SNP selection, and genotyping

All 735 participants donated a 3–5-mL blood sample and genomic DNA was isolated from samples using the phenol/chloroform method. We used resequencing to carry out systematic screening in the promoter and all the exon regions of the UHRF1 gene. The sequences of the PCR primers are given in Additional file 1: Table S1. PCR was carried out in a 15-μL reaction mixture containing 10 ng of DNA, 10 pmol of each primer, 2.5 mM MgCl2, 0.2 mM dNTP and 0.25 U Taq DNA polymerase. All reactions had an initial denaturation step of 3 min at 94 °C, followed by 35 cycles of 94 °C for 30 sec denaturation, annealing at the specific annealing Tm for 30 sec and 72 °C for 1 min, and finally at 72 °C for 10 min on a Gene Amp PCR system 9700 (Applied Biosystems, Foster City, CA). Preparation of DNA for sequencing included incubation of PCR products with 0.1 U of shrimp alkaline phosphatase (Roche, Basel, Switzerland) and 0.5 U of exonuclease I (New England Biolabs Inc., Beverly, MA) at 37 °C for 45 min, followed by heat inactivation at 85 °C for 20 min to remove primers. Cycle sequencing was carried out using a volume of 10 mL containing 50–100 ng of concentrated PCR product DNA purified in a 96-well filtration plate (Millipore, Bedford, USA) with 3.2 pmol of either sense or antisense primer in the GeneAmp 9700 thermocycler (PE Applied Biosystems, Perkin-Elmer) and a BigDye Terminator Cycle Sequencing Ready Reaction Kit (PE Applied Biosystems, Perkin-Elmer). The sequences were analyzed in an ABI PRISM model 3700 DNA Sequencer (PE Applied Biosystems, Perkin-Elmer) to determine the genotypes of variation at the same position on both forward and reverse sequences.

Plasmid constructs: promoter reporter vectors

The wild-type 1742-bp fragment of the human UHRF1 promoter region (− 2091 to − 349, relative to the transcriptional start codon) and its two mutant forms were generated by de novo chemical synthesis. Each mutant form contains one SNP (-1615C>T-C, and -1562A>G-A). The constructions including the SNPs were confirmed by sequencing. Then, the three fragments were amplified using the following polymerase chain reaction (PCR) primers: the Kpn I site-linked primer, 5′-TTTCTCTATCGATAGGTACCGAGACTGAGTTTTGCTTTTGTTGC-3′, as a forward primer and the Xho I site-linked primer, 5′-CTTAGATCGCAGATCTCGAGGGGAGTTGCGGGGCCGCAGGAG-3′, as a reverse primer. Finally, these fragments were cloned to the GV238 luciferase vector (GeneChem).

Transfection and luciferase activity analysis

The 293T cells were cultured in Dulbecco Modified Eagle Medium supplemented with 10% fetal bovine serum, 100 U/mL penicillin and 100 μg/mL streptomycin at 37 °C under 5% CO2. The cells were seed on 96-well plates 24 hours before transfection.

Luciferase assay was performed in order to study the effects of SNPs on the UHRF1 promoter activity. These wild type or mutated constructs were transiently transfected into 293T cells using X-tremeGENE HP transfection reagent (Roche, Sweden) according to the technical guide of product. The cells were collected 48 h after transfection and assayed for firefly and Renilla luciferase expression using the Dual-Luciferase Reporter Assay System (Promega) to detect the relative luciferase activity and reflect the transcriptional activity of the promoter. Renilla luciferase activities were normalized to firefly luciferase activity.

Prediction of the functional elements of the 5′-flanking region

The JASPAR database (http://jaspar.genereg.net/) and Promoter Scan (http://www-bimas.cit.nih.gov/molbio/proscan/) were used to predict transcription factors (TFs).

Statistics

All experiments were repeated at least three times. Data from the luciferase assay are expressed as the mean ± standard deviation. Statistical analyses were carried out using SPSS version 22.0 software (SPSS, Inc., Chicago, IL, USA). Genotypic or allele frequencies between cases and controls were compared using the χ2 test. A haplotype block was inferred from analysis of linkage disequilibrium [25] between polymorphisms using Haploview 4.2, assuming a scheme based on the representation of the confidence interval of the normalized linkage disequilibrium coefficient (D′). The Chi-squared test was used to analyze the frequencies of the obtained haplotypes between groups [31]. The odds ratio (OR) and their 95% confidence intervals (CI) were estimated for the effects of the alleles. Analysis of variance was used to compare differences in means between the variants and their controls. P < 0.05 was considered to indicate a statistically significant difference. Data were log-transformed before analysis of variance to satisfy the equal variances assumption.

Results

Identification of UHRF1 variants in patients

Twenty-four SNPs in the UHRF1 gene were identified in 342 normozoospermic men and 393 oligozoospermia patients by sequencing. The locations of these 24 variants within the UHRF1 are presented in Fig. 1. The allele and genotype frequencies determined in the analysis of UHRF1 genetic variants are shown in Table 1. The 24 SNPs, including nine SNPs in the promoter region, three SNPs in 5′ untranslated regions, five SNPs in introns, and seven SNPs in exons were identified. Moreover, eight novel SNPs were detected. Four were in the UHRF1 promoter region and the other four were in introns and have not been reported as genetic polymorphisms in the public database dbSNP135 (www.ncbi.nlm.nih.gov/projects/SNP/) or 1000 Genome Project dataset (www.internationalgenome.org/home). Additionally, as shown in Table 1, seven synonymous variants were detected in four exons.

Fig. 1.

Fig. 1

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Genomic structure and locations of polymorphic sites in the human UHRF1 gene. This gene is on chromosome 19p13.3 and contains 17 exons. We carried out a systematic study of the promoter, exon, and intron regions of UHRF1 by direct sequencing and detected 24 SNPs. We selected 16 SNPs with high allele frequencies (> 5%) for allele and genotype frequency analysis. Eight SNPs (highlighted) were only detected in cases or controls, 2 SNPs (marked with red color) were only detected in patients and were screened and tested in the luciferase assay, and 2 SNPs (marked in green color) in intron regions were only detected in patients and were not further tested

Table 1.

Summary of genetic variations detected in the UHRF1 gene

Position NG_033256.2position dbSNP Sequence variants Codon change Amino acid change
Promoter region Chr19:4907815 rs569696237 -1615C>T
Promoter region Chr19:4907868 New -1562A>G
Promoter region Chr19:4907956 rs375487487 -1474C>A
Promoter region Chr19:4907982 New -1448G>A
Promoter region Chr19:4908003 rs4807663 -1427C>T
Promoter region Chr19:4908009 New -1421G>A
Promoter region Chr19:4908034 New -1396C>G
Promoter region Chr19:4908081 rs4807664 -1349T>G
Promoter region Chr19:4908263 rs2656927 -1167C>T
5′UTR Chr19:4909617 rs8103849 -49C>G
5′UTR Chr19:4909640 New -26C>T
Intron Chr19:4909758 New -11+103C>T
Intron Chr19:4909790 rs557510777 -11+135C>T
Intron Chr19:4909995 New -11+340C>T
Intron Chr19:4910009 rs2602713 -11+354A>C
Intron Chr19:4910062 New -11+407C>G
5′UTR Chr19:4910877 rs2261988 -9G>T
Exon 2 Chr19:4910912 rs2261986 c.27C>T GAC>GAT Asp9Asp
Exon 3 Chr19:4929401 rs2251520 c.333T>C GGT>GGC Gly111Gly
Exon 3 Chr19:4929461 rs2123731 c.393A>G GAA>GAG Glu131Glu
Exon 10 Chr19:4945902 rs2250982 c.1347A>C ATA>ATC Ile449Ile
Exon 10 Chr19:4945902-4945905 rs386806190 c.1347_1350delACACinsCCAT ACAC>CCAT Ile449_His450=
Exon 10 Chr19:4945962 rs2250978 c.1407T>C GAT>GAC Asp469Asp
Exon 12 Chr19:4950758 rs2307213 c.1665C>T TAC>TAT Tyr555Try
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To analyze the combined effect of UHRF1 SNPs on oligozoospermia development, we investigated linkage disequilibrium (LD) [25] for all possible two-way comparisons among all SNPs in UHRF1 (Fig. 2). However, we found that the genotypic distribution of rs2602713 was not in Hardy-Weinberg equilibrium. When analyzing the LD and common haplotype patterns of all 15 SNPs (among all 24 SNPs, 8 were only found in healthy controls or patients, and rs2602713 was not tested), to search for systematically novel associations and validate our results for the variants within UHRF1, we identified one haplotype block in which rs4807663, rs4807664, rs2656927, rs375487487, rs8103849, a new SNP (chr19:4909640), and rs557510777 in the UHRF1 gene showed strong relationships (|D′| > 0.8) (Fig. 2). Particularly, the CTCCCCC (P = 0.012) and CTCCGCC (P = 0.012) haplotypes were associated with oligozoospermia.

Fig. 2.

Fig. 2

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Estimates of linkage disequilibrium (LD) [25] statistics between all pairs of markers. The numbers in the diamond-shaped cells are values (× 100). The shades of pink colors from white to red in the diamond-shaped cells correspond to values from 0 to 1. a All detected SNPs in LD in cases (sperm density < 20 × 106/mL) and controls (sperm density ≥ 20 × 106/mL). b Block of -1427C>T, -1349T>G, -1167C>T, -1474C>A, -49C>G, -26C>T, and -11+135C>T in LD in cases (sperm density < 20 × 106/mL) and controls (sperm density ≥ 20 × 106/mL). c Block of -49C>G, -26C>T, -11+135C>T, -9G>T, and c.27C>T in LD in cases (sperm density < 20 × 106/mL) and controls (sperm density ≥ 20 × 106/mL)

In the case-control study, we evaluated the genotype frequencies of 15 SNPs in allele and genotype frequency analysis in 342 normal men and 393 patients with oligozoospermia in the UHRF1 gene (Table 2). Adjusted ORs and 95% CIs for the associations between idiopathic male infertility and 15 SNPs are presented in Table 2. The distribution of polymorphisms was in Hardy–Weinberg equilibrium. rs2656927 (P = 0.014) and rs8103849 (P < 0.001) were found to significantly differ between case group 1 and fertile men. Genotypes and alleles of the other SNPs in the UHRF1 gene showed no significant association with infertility.

Table 2.

Allele and genotype frequencies in UHRF1 genetic variant analysis in men with oligozoospermia (n = 393) and healthy controls (n = 342)

NG_033256.2 position RS ID Group Number of genotypes and genotype frequency (Freq.) P value Number of alleles and allele frequency (Freq.) OR (95% CI)
Chr19:4908003 rs4807663 CC CT C T
Case 1a 283 (0.979) 6 (0.021) 0.557 572 (0.990) 6 (0.010) 0.70 [0.213–2.312]
Case 2b 104 (1.000) 0 (0.000) 0.215 208 (1.000) 0 (0.000) -
Control 337 (0.985) 5 (0.015) 679 (0.993) 5 (0.007)
Chr19:4908081 rs4807664 GT TT G T
Case 1a 20 (0.069) 269 (0.931) 0.117 20 (0.035) 558 (0.965) 1.72 [0.859–3.427]
Case 2b 3 (0.029) 101( 0.971) 0.573 3 (0.014) 205 (0.986) 0.70 [0.196–2.470]
Control 14 (0.041) 328 (0.959) 14 (0.020) 670 (0.980)
Chr19:4908263 rs2656927 CC CT C T
Case 1a 289 (1.000) 0 (0.000) 0.014 578 (1.000) 0 (0.000) -
Case 2b 103 (0.990) 1 (0.010) 0.465 207 (0.995) 1 (0.005) 2.14 [0.262–17.498]
Control 335 (0.980) 7 (0.020) 677 (0.990) 7 (0.010)
Chr19:4907956 rs375487487 AC CC A C
Case 1a 14 (0.048) 275 (0.952) 0.209 14 (0.024) 564 (0.976) 1.67 [0.737–3.780]
Case 2b 3 (0.029) 101 (0.971) 0.983 3 (0.014) 205 (0.986) 0.99 [0.269–3.618]
Control 10 (0.029) 332 (0.971) 10 (0.015) 674 (0.985)
Chr19:4909617 rs8103849 CC CG C G
Case 1a 273 (0.945) 16 (0.055) < 0.001 562 (0.972) 16 (0.028) 3.01 [1.704–5.320]
Case 2b 88 (0.846) 16 (0.154) 0.921 192 (0.923) 16 (0.077) 1.03 [0.575–1.839]
Control 288 (0.842) 54 (0.158) 630 (0.921) 54 (0.079)
Chr19:4909640 New CC CT C T
Case 1a 289 (1.000) 0 (0.000) 0.065 578 (1.000) 0 (0.000) -
Case 2b 104 (1.000) 0 (0.000) 0.268 208 (1.000) 0 (0.000) -
Control 338 (0.988) 4 (0.012) 680 (0.994) 4 (0.006)
Chr19:4909790 rs557510777 CC CT C T
Case 1a 284 (0.983) 5 (0.017) 0.171 573 (0.991) 5 (0.009) 0.336 [0.065–1.738]
Case 2b 104 (1.000) 0 (0.000) 0.434 208 (1.000) 0 (0.000) -
Control 340 (0.994) 2 (0.006) 682 (0.997) 2 (0.003)
Chr19:4910877 rs2261988 GG GT TT G T
Case 1a 110 (0.873) 15 (0.119) 1 (0.008) 0.636 235 (0.933) 17 (0.067) 1.31 [0.748–2.292]
Case 2b 75 (0.798) 17 (0.181) 2 (0.021) 0.556 167 (0.888) 21 (0.112) 0.75 [0.445–1.275]
Control 288 (0.845) 47 (0.138) 6 (0.018) 623 (0.913) 59 (0.087)
Chr19:4910912 rs2261986 CC CT TT C T
Case 1a 110 (0.873) 15 (0.119) 1 (0.008) 0.636 235 (0.933) 17 (0.067) 1.31 [0.748–2.292]
Case 2b 75 (0.798) 17 (0.181) 2 (0.021) 0.556 167 (0.888) 21 (0.112) 0.75 [0.445–1.275]
Control 288 (0.845) 47 (0.138) 6 (0.018) 623 (0.913) 59 (0.087)
Chr19:4929401 rs2251520 CC CT TT C T
Case 1a 4 (0.032) 19 (0.151) 103 (0.817) 0.444 27 (0.107) 225 (0.893) 0.957 [0.601–1.523]
Case 2b 1 (0.011) 15 (0.160) 78 (0.830) 0.721 17 (0.090) 171 (0.910) 0.79 [0.456–1.377]
Control 6 (0.018) 64 (0.188) 271 (0.795) 76 (0.111) 606 (0.889)
Chr19:4929461 rs2123731 AA AG GG A G
Case 1a 103 (0.817) 19 (0.151) 4 (0.032) 0.444 225 (0.893) 27 (0.107) 1.05 [0.656–1.664]
Case 2b 79 (0.840) 14 (0.149) 1 (0.011) 0.598 172 (0.915) 16 (0.085) 1.35 [0.766–2.372]
Control 271 (0.795) 64 (0.188) 6 (0.018) 606 (0.889) 76 (0.111)
Chr19:4945902 rs2250982 AA AC A C
Case 1a 125 (0.992) 1 (0.008) 0.929 251 (0.996) 1 (0.004) 1.11 [0.115–10.711]
Case 2b 94 (1.000) 0 (0.000) 0.362 188 (1.000) 0 (0.000) -
Control 338 (0.991) 3 (0.009) 679 (0.996) 3 (0.004)
Chr19:4945902-4945905 rs386806190 AA CC A C
Case 1a 17 (0.135) 109 (0.865) 0.237 34 (0.135) 218 (0.865) 1.46 [0.936–2.264]
Case 2b 6 (0.064) 88 (0.936) 0.322 12 (0.064) 176 (0.936) 0.64 [0.336–1.204]
Control 33 (0.097) 308 (0.903) 66 (0.097) 616 (0.903)
Chr19:4945962 rs2250978 CC CT TT C T
Case 1a 123 (0.976) 0 (0.000) 3 (0.024) 0.172 246 (0.976) 6 (0.024) 0.36 [0.116–1.139]
Case 2b 94 (1.000) 0 (0.000) 0 (0.000) 0.573 188 (1.000) 0 (0.000) -
Control 337 (0.988) 2 (0.006) 2 (0.006) 676 (0.991) 6 (0.009)
Chr19:4950758 rs2307213 CC CT TT C T
Case 1a 55 (0.437) 57 (0.452) 14 (0.111) 0.350 167 (0.663) 85 (0.337) 1.23 [0.905–1.660]
Case 2b 43 (0.457) 38 (0.404) 13 (0.138) 0.198 124 (0.660) 64 (0.340) 1.21 [0.861–1.696]
Control 124 (0.364) 172 (0.504) 45 (0.132) 420 (0.616) 262 (0.384)
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aCase 1 (case group 1): idiopathic infertile men with sperm concentration < 15 × 106/mL

bCase 2 (case group 2): idiopathic infertile men with sperm concentration (15–20) × 106/mL

Association of gene polymorphisms with semen quality variables

The semen density among fertile subjects was 62.22 ± 1.36 × 106/mL, while that in case group was 10.43 ± 0.27 × 106/mL. As shown in Table 2, we found a significant difference only between case group 1 and fertile men. Thus, we analyzed the effects of the 15 genetic variations on semen quality variables in case group 1 using SPSS software (Table 3). We compared the association of sperm parameters (sperm density, progressively motile sperm (PMS), non-progressively motile sperm (NMS), and PMS + NMS) in patients with oligozoospermia with 15 SNPs genotypes. The results showed patients with the CG genotype of rs8103849 had significantly higher sperm density (P < 0.05) than those with the wild-type genotypes. Additionally, the CG genotype of rs8103849 carriers showed more progressively motile sperm (P = 0.049), non-progressively motile sperm (P = 0.012), and PMS + NMS (P = 0.034) compared with controls.

Table 3.

Association between different genotypes of UHRF1 and semen quality traits of Chinese infertile males with sperm density < 15 × 106/mL (mean ± standard error)

SNP Genotype Case group 1a
Sperm density (million/mL) Progressively motile sperm (%) Non-progressively motile sperm (%) PMS + NMS (%)b
rs4807663 CC 8.23 ± 0.25 5.72 ± 0.38 8.72 ± 0.40 14.35 ± 0.76
CT 7.03 ± 1.80 4.60 ± 1.78 7.80 ± 2.33 12.40 ± 4.03
rs4807664 TT 8.12 ± 0.26 5.64 ± 0.40 8.59 ± 0.41 14.15 ± 0.78
GT 9.31 ± 0.89 6.42 ± 1.23 10.21 ± 1.45 16.63 ± 2.58
rs2656927 CC 8.20 ± 0.25 5.70 ± 0.38 8.70 ± 0.40 14.32 ± 0.75
CT 0.00 0.00 0.00 0.00
rs375487487 CC 8.19 ± 0.26 5.75 ± 0.39 8.76 ± 0.41 14.42 ± 0.78
AC 8.43 ± 1.13 4.71 ± 1.35 7.64 ± 1.45 12.36 ± 2.67
rs8103849 CC 7.98 ± 0.26 5.47 ± 0.38 8.43 ± 0.40 13.86 ± 0.76
CG 12.13 ± 0.35A** 9.73 ± 1.90A* 13.47 ± 2.06A* 21.75 ± 3.84A*
chr19:4909640 CC 8.20 ± 0.25 5.70 ± 0.38 8.70 ± 0.40 14.32 ± 0.75
CT 0 0 0 0
rs557510777 CC 8.20 ± 0.25 5.70 ± 0.38 8.68 ± 0.40 14.29 ± 0.76
CT 8.44 ± 3.02 5.80 ± 1.80 9.80 ± 3.25 15.60 ± 4.98
rs2250982 AA 11.80 ± 0.14 7.45 ± 0.66 10.29 ± 0.66 17.52 ± 1.27
AC 14.00 2.00 4.00 6.00
rs386806190 CC 11.76 ± 0.15 7.58 ± 0.74 10.26 ± 0.71 17.67 ± 1.39
AA 12.18 ± 0.35 6.35 ± 1.23 10.13 ± 1.70 15.88 ± 2.88
rs2261988 GG 11.72 ± 0.15 6.92 ± 0.68 9.74 ± 0.67 16.56 ± 1.29
GT 12.40 ± 0.36 11.43 ± 2.24 14.07 ± 2.30 23.80 ± 4.47
TT 14.00 4.00 10.00 14.00
rs2261986 CC 11.72 ± 0.15 6.92 ± 0.68 9.74 ± 0.67 16.56 ± 1.29
CT 12.40 ± 0.36 11.43 ± 2.24 14.07 ± 2.30 23.80 ± 4.47
TT 14.00 4.00 10.00 14.00
rs2251520 TT 11.83 ± 0.16 7.00 ± 0.72 9.77 ± 0.70 16.68 ± 1.37
CT 11.89 ± 0.38 8.69 ± 1.54 12.00 ± 2.08 19.47 ± 3.50
CC 11.00 ± 0.00 12.75 ± 4.19 15.00 ± 2.89 27.75 ± 7.08
rs2123731 AA 11.83 ± 0.16 7.00 ± 0.72 9.77 ± 0.70 16.68 ± 1.37
AG 11.89 ± 0.38 8.69 ± 1.54 12.00 ± 2.08 19.47 ± 3.50
GG 11.00 ± 0.00 12.75 ± 4.19 15.00 ± 2.89 27.75 ± 7.08
rs2250978 CC 11.82 ± 0.14 7.45 ± 0.67 10.20 ± 0.66 17.42 ± 1.28
CT 0 0 0 0
TT 11.67 ± 0.88 6.00 ± 3.00 11.67 ± 4.41 17.67 ± 7.31
rs2307213 CC 11.82 ± 0.22 7.52 ± 1.12 9.85 ± 1.04 17.37 ± 2.08
CT 11.88 ± 0.21 7.52 ± 0.95 10.56 ± 0.96 17.75 ± 1.86
TT 11.57 ± 0.34 6.57 ± 1.00 10.54 ± 1.61 16.36 ± 2.57
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Results are presented as the mean ± SD. PMS, progressively motile sperm; NMS, non-progressively motile sperm

aIdiopathic infertile men with sperm concentration < 15 × 106/mL

bGrade of sperm movement according to WHO [2010] criteria

AVariant vs. wild type

*P < 0.05

**P < 0.001

Effect of SNPs on binding of transcriptional factors

As shown in Table 1, four variants were detected only in patients, with two in the promoter region and two in introns. We predicted that the two patient-only mutants in the promoter affect TF binding and UHRF1 expression. The TFs which bind the UHRF1 promoter region (− 1921 to + 145) were previously reported [32]. We evaluated whether the SNPs in the UHRF1 promoter region affect the interaction of TFs and cis-elements in the UHRF1 promoter. According to our analysis based on the JASPAR program, these two patient-only SNPs may bind to 21 TFs (Additional file 2: Table S2). Many binding sites for transcription factors, including SP1, Meis1, GATA2, TFAP2A, and sterol regulatory element-binding transcription factor 2 (SREBF2), among others, were predicted to be present in these two SNP regions. These results suggest that the SNPs affect UHRF1 expression by disturbing the interactions between the promoter and diverse TFs.

Effects of SNPs on UHRF1 promoter activity

To investigate whether the two mutants (-1615C>T-C and -1562A>G-A) in the promoter region affect UHRF1 promoter activity, the -1615C>T-C and -1562A>G-A promoter regions and UHRF1 promoter were synthesized and cloned into the GV238 vector, resulting in a GV238-promoter, -1615C>T-C, and -1562A>G-A, which were transfected into 293T cells. The results indicated that the luciferase activity of the plasmid GV238-promoter was greater than that of plasmids -1615C>T-C and -1562A>G-A in 293T cells (P < 0.05; Fig. 3). These results indicate that the two mutations in the promoter region affected the promoter activity of the Chinese male UHRF1 gene by repressing TF interactions.

Fig. 3.

Fig. 3

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Function of two SNPs in the UHRF1 promoter region. Transactivation activity of WT and two UHRF1 mutant promoters. The GV238 and WT or mutant UHRF1 promoters were co-transfected into 293T cells. UHRF1 promoter activity was analyzed by luciferase assay. NC: GV238 empty vector was transfected into 293T cells as a negative control. Fold change is shown as the ratio of WT or mutants to the average of NC

Discussion

In this study, we investigated whether genetic variations in UHRF1 were associated with oligozoospermia. We scored genetic variations in a large case-control sample (393 oligozoospermia cases, 342 healthy controls). A total of 24 SNPs in the UHRF1 gene were detected. Both rs2656927 and rs8103849 were more frequent in control subjects, suggesting that they protect against infertility. Consistent with this hypothesis, rs8103849 was found to be associated with sperm density, progressively motile sperm, non-progressively motile sperm, and PMS + NMS. Importantly, two SNPs (-1615C>T-C and -1562A>G-A allele) were detected only in patients. In vitro analysis revealed that the two variants reduced UHRF1 promoter activity. Given that deficiency of the UHRF1 gene severely damages mouse spermatogenesis [30], our results strongly suggest that the two genetic variations in UHRF1 result in oligozoospermia by lowering UHRF1 expression. Studies of the SNPs in UHRF1 genes have not been reported previously.

Aberrant sperm DNA methylation likely occurs because of low expression of UHRF1, as UHRF1 is currently the only protein identified to recruit DNMT1 to hemimethylated CG sites. Knockout of UHRF1 significantly reduced the overall level of DNA methylation in male germ cells [30], oocytes [33], and diverse somatic cells, whereas DNA methylation at imprinting control regions is particularly sensitive to UHRF1 deficiency [33]. Therefore, the inheritance of these SNPs in UHRF1 may result in hypomethylation of the genome when the epigenetic pattern is established in early development. The persistence of altered DNA methylation patterns in the germline may, therefore, increase the risk of infertility. The association between these genetic variations in UHRF1 and the risk of aberrant methylation of imprinted genes should be further evaluated in oligozoospermia. Although genetic variations in DNMT1 are associated with male infertility [14, 17], no studies have evaluated whether the SNPs in DNMT1 are associated with altered DNA methylation. However, Louie et al. recently reported that the MTHFR C677T genotype, which reduces synthesis of the methyl donor, was not predictive of altered DNA methylation in spermatozoa [34].

Considering that the DNA-methylation-maintaining role of DNMT1-UHRF1 is completed during S phase of the cell cycle [35], high expression of UHRF1 not only in proliferating spermatogonia but also in meiotic spermatocytes and differentiating spermatids which were not proliferating [29] suggests that UHRF1 has different functions throughout spermatogenesis. Accordingly, these genetic variations of UHRF1 may contribute to the development of male infertility via other mechanisms besides DNA methylation, given that the protein contains multiple functional domains. For example, UHRF1 regulates DNA repair [36, 37], which depends on intrinsic E3 ligase activity in the Ring domain of UHRF1 [37]. Impaired DNA repair has been widely found to damage mouse spermatogenesis [38–40] and has been detected in oligozoospermia [41, 42]. Therefore, we predict that the fraction of sperm cells bearing double-strain breaks is significantly increased in the UHRF1-SNPs-positive oligozoospermic semen compared with that in semen from normozoospermic men. The hypothesis requires further analysis.

Currently, it remains unknown how these SNPs affect UHRF1 promoter activity. While numerous studies have been conducted to evaluate the function of UHRF1, the transcriptional regulation of UHRF1 has not been widely examined. The UHRF1 promoter region contains 5 YY1-binding motifs, and the occupation of YY1 at these sites represses transcription of the UHRF1 gene [32]. Interestingly, YY1 likely plays a role in maintaining the unmethylated status of these DMRs during spermatogenesis [43], supporting the hypothesis that YY1 regulates DNA methylation by down-regulating UHRF1.

Our analysis based on JASPAR suggested that the two SNPs (-1615C>T-C and -1562A>G-A) can bind to 21 TFs. Although the roles of most of these factors have not been reported in spermatogenesis, five (Meis1, GATA2, TFAP2A, SP1, and SREBF2) of these factors likely play important roles in SSCs [44–47]. Meis1 is a major transcriptional regulator controlling SSC-specific gene expression [48]. SP1 was reported to regulate the expression of SOHLH1 [49], which is required for the differentiation of SSC. NFIX silencing led to enhanced cell proliferation and DNA synthesis and reduced the early apoptosis of human SSCs [50]. These transcriptional factors may make different contributions to the self-renewal and/or differentiation of SSCs via regulating expression of UHRF1. Interestingly, p63 and p73, two members of p53 the family, are important for controlling the expression multiple genes throughout spermatogenesis [51, 52]. They likely contribute to the high expression of UHRF1 which was previously reported in differentiating spermatids [29]. Our study indicates that mutations in the UHRF1 gene are associated with male infertility, providing insight into the origin of widely altered DNA methylation in sperm from infertile men. Considering that some endocrine-disrupting chemicals exert male reproductive toxicity by affecting DNA methylation [53, 54], studies are needed to explore whether mutations in UHRF1 mediate the differential response of humans to exposure to diverse environmental factors.

Conclusion

We found that two SNPs in the UHRF1 gene may be associated with oligozoospermia and two patient-only SNPs in the 5′ untranslated region may affect UHRF1 promoter activity. Our findings suggested that the UHRF1 gene is involved in the pathology of male infertility with oligozoospermia.

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Abbreviations

SSC

spermatogonial stem cell

DNMT1

DNA methyltransferase I

PHD

plant homeodomain

UHRF1

ubiquitin-like containing plant homeodomain (PHD) and Ring Finger 1

SIPPR

Shanghai Institute of Planned Parenthood Research

WHO

World Health Organization

TF

transcription factor

SPSS

Statistical Package for the Social Sciences

OR

odds ratio

CI

confidence intervals

ANOVA

analysis of variance

LD

linkage disequilibrium

PMS

progressively motile sperm

NMS

non-progressively motile sperm

SNP

single-nucleotide polymorphism

UTR

untranslated region

SP1

specificity protein 1

SREBF2

sterol regulatory element-binding transcription factor 2

Authors’ contributions

WZ was responsible for the statistical analysis and wrote the manuscript. RL and JD contributed in conducting the study, designing the experiments, and writing, reviewing, and revising the manuscript. HS, BW, and JX acquired and managed the patients, collected the samples, and DNA preparation. TL, FZ, QC, and YB were responsible for DNA sequencing and analysis of promoter activity. All authors read and approved the final manuscript.

Funding information

This work was supported by grants from basic scientific research fund of Chongqing Population and Family Planning Science and Technology Research Institute (No. 1619 (QC, RL)), the National Natural Science Foundation of China (grant nos. 81571495, 81971443 (RL), 81571503, and 81771655 (JD)), Shanghai Municipal Committee of Science and Technology (15140903100 (RL)), and Innovation-Oriented Science and Technology Grant from NHC Key Laboratory of Reproduction Regulation (CX2017-07).

Data availability

The dbSNP and UCSC datasets generated and analyzed during the current study are available at http://genome.ucsc.edu/ and https://www.ncbi.nlm.nih.gov/snp/?term=. Other data generated and/or analyzed during this study are included in this article and its supplementary information files or are available on reasonable request.

Compliance with ethical standards

Competing interests

The authors declare that they have no competing interests.

Footnotes

Weiqiang Zhu and Jing Du are similar in author order.

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Huijuan Shi, Email: shihuijuan2011@163.com.

Runsheng Li, Email: runshengli2007@163.com.

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Data Availability Statement

The dbSNP and UCSC datasets generated and analyzed during the current study are available at http://genome.ucsc.edu/ and https://www.ncbi.nlm.nih.gov/snp/?term=. Other data generated and/or analyzed during this study are included in this article and its supplementary information files or are available on reasonable request.

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