The Assessment of Sperm DNA Integrity: Implications for Assisted Reproductive Technology Fertility Outcomes across Livestock Species
Abstract
:Simple Summary
Abstract
1. Introduction
2. DNA Maturation and the Development of Spermatozoa
2.1. Testicular Development
Susceptibility of Chromatin to Damage during Testicular Development
2.2. Epididymal Maturation and Fertilisation within the Female Reproductive Tract
3. Current Measures of DNA Integrity Used across Species
3.1. Sperm Chromatin Structure Assay (SCSA)
3.2. Single-Cell Gel Electrophoresis (COMET)
3.3. Transferase dUTP Nick End Labelling (TUNEL)
3.4. Chromomycin A3 (CMA3)
3.5. Toluidine Blue (TB)
3.6. Sperm Chromatin Dispersion (SCD) Test
3.7. 8-Hydroxyguanine
4. Implications for the Livestock Artificial Breeding Industry
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Assay | Predominant Species | Equipment | Technique | Advantages | Limitations |
---|---|---|---|---|---|
SCSA | Human, bull, ram, boar, and stallion | Flow cytometry | Measures susceptibility of sperm nuclear DNA to acid-induced denaturation. | Efficient, quantitative assessment. Has shown consistency in results. | Expensive equipment (flow cytometry) and skilled interpretation and training needed. |
TUNEL | Human, bull, stallion | Flow cytometry or microscopy | Labels free 3′-OH termini on ss-DNA or ds-DNA to detect DNA strand breaks and apoptosis. | High predictive value. Direct, easy to use and efficient. | Expensive equipment if flow cytometry used. Skilled equipment training needed. |
SCD | Human, ram, bull | Microscopy | Sperm subject to protein depletion treatment and assay relies on response of fragmented or unfragmented sperm DNA by lysis. | Simultaneously preserves sperm morphology. Simple and efficient. No expensive equipment cost. | Observer subjectivity |
COMET | Human, bull | Microscopy | Assesses level of SSB or DSB in a cell following agarose cell suspension, cell lysis, DNA denaturation, electrophoresis and microscopy. | Can be quantified to determine cells’ degree of DNA fragmentation. Can be used on a smaller population of cells. | Time-consuming. High level of training required to use specific computer programmes. No strong conclusions regarding fertility. |
TB | Human, bull | Microscopy | Metachromatic dye binds to damaged dense chromatin and phosphate groups of DNA strands. | Simple and inexpensive. Highly predictive of human fertility. | Labour intensive. Can only access a limited number of sperm cells. Observer subjectivity. |
CMA3 | Human, bull | Flow cytometry or microscopy | CMA3 compete for protamine binding sites to identify endogenous nicks in decondensed abnormal sperm. | Directly related to degree of protamination. Can identify abnormalities in histone–protamine displacement. | Observer subjectivity with microscopy. Expensive equipment if flow cytometry used. |
Species | ART Method | Sperm DNA Integrity Measure | Correlation/Outcome | Reference |
---|---|---|---|---|
SCA | ||||
Human (n = 165) | ICSI | DFI | DFI lower when pregnancy was achieved (14.86%) than when no embryonic heartbeat detected (17.37%); p = 0.031 Low DFI in spermatozoa corresponded with faster embryo development to reach the blastocyst stage DFI positively correlated with a delay in 8 out of 13 embryonic development periods | [86] |
Human (n = 420) | ICSI (OO or DO) | SDF before and after SU of fresh and frozen–thawed sperm | SDF increase of 10%; probability of negative pregnancy outcome increased by 1.31 SDF affects pregnancy outcome (OR 0.973, 95% CI 0.948–0.999, R2 0.069; p = 0.037) | [87] |
Human (n = 377) | ICSI | DFI >30% (mean 39.25) | DFI > 30% decreased number of 8-cell embryos on day 3 (3.97) Number of blastocysts formed on day 5 (1.6), CP (23.13%) and LB (13.43%) from <30% DFI (5.96, 2.44, 35.83%, 28.75%; n = 237); (p = 0.001, p = 0.001, p = 0.05, p = 0.005) Miscarriage rate (9.7%) increased from <30% DFI (7.08%); p = 0.005 | [88] |
Human (n = 135) | ICSI | SDF > 22.3% | SDF > 22.3% FR (55.1%) lower than sperm > 22.3% SDF (74.9%); p < 0.001. SDF negatively correlates with FR (r = −0.433; p < 0.001). | [89] |
Human (n = 94) | ICSI | Low DFI (<15%); (n = 50) Mod DFI (15–30%); (n = 31) High DFI (>30%); (n = 13) | High-DFI group was unable to achieve pregnancy following ICSI. | [90] |
Human (n = 85) | IVF/ICSI | SDF | SDF negatively correlated with FR (r = −0.241; p = 0.045) and implantation rate (r = −0.25; p = 0.042) of samples assessed post-capacitation Asymmetrical nuclei more frequent with increased SDF in capacitated sperm; p < 0.05 Higher SDF lowered ability to develop expanded blastocyts on d6; p < 0.05 | [91] |
Human (n = 867) | IVF (n = 379) | Low DFI (<30%); (n = 343) High DFI (>30%); (n = 36) | FR higher in High-DFI group (86.9%) than Low DFI (78.4%); p < 0.05 CP lower in High-DFI group (25%) than Low DFI (48.6%) p < 0.05 | [18] |
Rasa Aragonesa ram (n = 8) | Field fertility odds ratio 1.4–1.7 (HF; n = 4) 0.6–0.9 (LF; n = 4) | SDF | SDF following 6 and 24 h incubation at 37 °C higher in LF (20.27%, 31.24%) than HF (14.42%, 22.32%), p < 0.05, p < 0.01 | [92] |
Holstein bull (n = 201) | AI (≈533/bull) | SDF | SDF following 0 h incubation negatively correlates with ESBV and EGV (r = −0.45, r = −0.36; p < 0.0001) SDF following 6 h incubation negatively correlates with ESBV and EGV (r = −0.49, r = −0.38; p < 0.0001) | [93] |
Stallion (n = 11) Moderate fertility = PR <50% (n = 8) Good fertility = PR >50% (n = 3) | Uterine AI (catheter) | SDF in semen cool-stored in spring vs. summer | Negative correlation between SDF and PR (r = −0.619; p < 0.001) Moderate-fertility group has higher SDF at 0 (7.9) and 6 h (15.4) cooled storage compared to good-fertility group (3.83%, 9.58%); p < 0.05 SDF rate higher in sperm cool-stored in summer than in spring and PR lower in summer than spring; p < 0.05 | [94] |
TUNEL | ||||
Human (n = 105) | ICSI | DFI > 20% (% TUNEL positive) | DFI > 20% decreased the number of good-quality embryos (6.63), implantation rate (4.9%), and number of pregnancies (3) from <20% DFI (11, 15.79%, 9); p = 0.018, p = 0.002, p = 0.046 | [95] |
Human (n = 36) | ICSI | SDF | SDF negatively correlated with mean total embryo score (r = −0.64, p < 0.001) and mean transferred embryo score (r = −0.63, p < 0.001) SDF TH 17.6% is predictive of pregnancy (p < 0.021) | [96] |
Human (n = 303) | IVF/ICSI | SDF | SDF higher in ICSI (6.8%) than IVF (1.9%) group (p < 0.05) SDF negatively correlated with IVF and ICSI FR (r = −0.357; p < 0.001, r = −0.222; p = 0.04) Good embryo rate (p < 0.05) SDF <4% (46.4%) higher than 10–15% SDF (31.6%) in IVF group SDF <4% (45.6%) higher than 10–15% SDF (33.0%) in all samples | [97] |
Human (n = 45) | IVF | SDF (%TUNEL positive) | SDF negatively correlated with FR; p < 0.05 >55% SDF resulted in lower FR than <35% SDF; p < 0.05 | [98] |
Human (n = 68) | ICSI | SDF (%TUNEL positive) | SDF higher in non-pregnant group than pregnant group | [98] |
Holstein bulls (n = 5) | AI | SDF (% TUNEL positive) | SDF higher in LF (below-average fertility) bulls (20–25%) than average or HF (above-average fertility) bulls (<15%); p < 0.05 | [99] |
Norwegian red bulls (n = 30) | AI | SDF (% TUNEL positive) 4.8–9.4% 9.4–21.2% | 2.2–4.8% SDF 10% significantly higher odds of AI success (p = 0.006) | [100] |
SCSA | ||||
Human (n = 2262) | ART (AIH-IUI n = 1185, IVF n = 1221, ICSI n = 216) | High DFI (≥30%) Med DFI (15–30%) Low DFI (≤15%) | AIH-IUI: Early abortion rate increased in High-DFI (27.3%) and Med-DFI (14.6%) groups compared to Low DFI (4.9%); p < 0.05 | [101] |
Human (n = 1316) | IVF | DFI >11.3% | DFI higher in non-pregnant (17%) than pregnant group (14.9%); p = 0.001 DFI is a predictor of pregnancy outcome (p = 0.023) DFI TH > 11.3% is predictive of pregnancy outcome (AUCROC 0.574, 95% CI 0.541–0.607, SE 56.1%, SP 60%, PPV 77.9%, NPV 35.1%) | [102] |
Human (n = 266) | ICSI | DFI >30.3% | DFI higher in non-pregnant (31.5%) than pregnant group (26.3%); p = 0.01 DFI is a predictor of pregnancy outcome (p = 0.004) DFI TH > 30.3% is predictive of pregnancy outcome (AUCROC 0.567, 95% CI 0.487–0.647, SE 50.6%, SP 68.8%, PPV 79.3%, NPV 37.0%) | [102] |
Human (n = 96) | ICSI (n = 155) | 19% DFI TH | DFI TH ≥ 18–19% predicts the outcome of ICSI (p < 0.005) DFI negatively correlates with continuing pregnancies (r = −0.184, p = 0.022), and positively correlates with non-pregnancy (r = 0.197, p = 0.014) Continuing pregnancy rate and implantation rate lower in ≥19% DFI group (14.9%, 12.1%) than <19% DFI (34.6%, 27.2%); p = 0.005, 0.001 Non-pregnancy rate significantly higher in ≥19% DFI group (75.7%) than <19% DFI (55.6%) p = 0.008 | [103] |
Ram (n = 15) | Vaginal AI | Mean DFI and heterogeneity (SD DFI) of SDF in the total sperm population | Mean DFI negatively associated with 25 d NRR (OR 0.98, 95% CI 0.97–1, p = 0.039) SD DFI negatively associated with 25 d NRR (OR 0.98, 95% CI 0.97–0.99, p = 0.001 | [16] |
Finnish Ayrshire bull (n = 43) >55% 60 d NRR (F; n = 21) <55% 60 d NRR (SF; n = 22) | AI (n ≈ 5964/bull) | DFI SD-DFI HDS | HDS higher in F (0.61%) than SF bulls (0.48%); p < 0.05 HDS positively correlated with calving rate (r = 0.31; p < 0.05) | [12] |
Norwegian red bull (HF; n = 19) (LF; n = 18) | AI | DFI HDS | HF bulls had lower DFI and HDS (1.84%, 2.93%) than LF bulls (3.5%, 4.31%) p < 0.01 DFI and HDS negatively correlate with 56 d NRR56 (r = −0.57, p = 0.0003, r = −0.37, p = 0.026) DFI significantly predicts 56 d NRR (p < 0.01) | [104] |
Norwegian red bulls (n = 30) | AI | DFI | 7.5–21.6% DFI reduced odds of AI success from average (6%; p = 0.011) 1.6–3.8% DFI increased odds of AI success from average (7%; p = 0.010) | [100] |
Swedish red bull (n = 14) Holstein bull (n = 6) | AI | DFI 3.31% TH Below-average 56 d NRR (BAB, n = 5) Average 56 d NRR (AB, n = 9) Above-average 56 d NRR (AAB, n = 6) | DFI decreased in AAB (2.88%) compared to BAB and AB (6.23%, 4.65%); p < 0.05 DFI negatively correlated with adjusted 56 d NRR (r = −0.61; p = 0.01) DFI can differentiate between BAB and AAB (R2 = 0.56; p = 0.02) DFI TH 3.31% accurately predicts 56 d NRR (SE 66.7%, SP 100%, AUCROC 0.8) | [11] |
Holstein bulls (n = 20) | AI | DFI (COMP αt) | DFI negatively correlated to NRR (r = −0.60 p < 0.01) DFI lower in mature bulls than in young bulls (p < 0.01) | [105] |
Holstein bulls (n = 19) | AI (n = 192) | SDF | SDF negatively correlated with 56 d NRR (r = −0.287, r2 = 0.082; p < 0.05) | [106] |
Bulls: Holstein (n = 156) Jersey (n = 39) | AI (n = 75,610) | DFI SD-DFI HDS | Sperm without DFI (97.5%) predicts 56 d NRR (p < 0.0001) Sperm with moderate DFI (2.4%) predicts 56 d NRR (p < 0.0001) Sperm with High DFI (0.2%) predicts 56 d NRR (p < 0.0003) SD-DFI (33.3%) predicts 56 d NRR (p < 0.0001) HDS (2.8%) predicts 56 d NRR (p < 0.0004) | [107] |
Boar (n = 18) | AI | Mean DFI SD DFI of SDF in the total sperm population | DFI negatively correlated with farrowing rate (r = −0.55, p < 0.01) and ANB (r = −0.54, p < 0.01) SD DFI negatively correlated with farrowing rate (r = −0.67, p < 0.002) and ANB (r = −0.54, p < 0.02) DFI TH 6% is predictive of farrowing rate and ANB (OR 1.5, 95% CI 1.21–1.94, p = 0.0003, SE 83%) SD DFI TH 40 is predictive of farrowing rate and ANB (OR 2.5, 95% CI 1.87–3.32, p = 0.001, SE 92%) | [15] |
Boar (n = 160) | AI | DFI > 3% DFI > 2.1% | DFI > 3% (0 h storage) reduced ANB/litter (13.9) from DFI < 3% (14.87–14.94); p < 0.01 For Landrace and Danish Large White boars, DFI > 2.1% after 24 h 18 °C storage had lower litter size (14.4, 14.2) than DFI < 2.1% (15.1, 15.1); p < 0.01 | [108] |
Stallion (n = 41) | AI | DFI SD DFI Mean DFI | DFI negatively correlated with PR (r = −0.63, p < 0.05) | [109] |
COMET | ||||
Human (n = 339) | IVF (n = 203) ICSI (n = 136) | >50% SDF (Comet Score) TH | SDF higher in non-pregnant group than LB or miscarriage groups (p < 0.05) following IVF SDF TH > 50% reduced pregnancy (16.2, p = 0.005) and LB rates (13.1%, p = 0.007) following IVF | [110] |
Bulls (n = 45) | IVP (-ET) | Mean-DNA Mean H-DNA T-DNA | T-DNA higher in group 4 (8.53%) than group 3 (4.31%); p < 0.05 Mean-DNA and Mean H-DNA negatively correlated with blastocyst rate (r = −0.375, r = 0.389; p = 0.02, p = 0.016) | [111] |
Italian Mediterranean Buffalo bulls (n = 3) | AI (n = 528) | % H-DNA % T-DNA TM OTM | % H-DNA TH ≥ 86% (and its relative % T-DNA < 14%) predicts successful d30/45 pregnancy (AUCROC 0.56, SE 81%, SP 26%; p < 0.05) Tail area TH ≤ 58 μm2 predicts successful d30/45 pregnancy (AUCROC 0.56, SE 80%, SP 26%; p < 0.05) | [112] |
Nili–Ravi Water Buffalo bull (n = 5) | AI (n = 514) | Comet length, % H-DNA, %T-DNA, tail length, TM, OTM | Tail length negatively correlated with fertility rate (r = −0.7; p = 0.04) | [113] |
Buffalo bulls (n = 6) (HF; n = 3) (LF; n = 3) | IVP (-ET) | SDF (% of cells comet tail+) | SDF higher in LF group (18.72%) than HF group (8.94%; p < 0.05). | [114] |
TB | ||||
Humans (n = 1386) | Infertile and normospermic | SDF% | Mean TB staining was higher in infertile group than normospermic (p = 0.005) | [115] |
Human (n = 142) | Infertile and fertile men | %TB dark cells %TB light cells | TB dark cells and light cells had 92% and 90% specificity, respectively, for predicting infertility Both poor predictors of fertility (42 and 32% sensitivity, respectively) | [116] |
Bull (n = 8) | Fertile and sub-fertile (subjects to scrotal insulation) | Chromatin alteration types (Base, Basal half, Central axis, Dispersed and Whole) | Greater (p < 0.01) chromatin decondensation and heterogeneity were recorded in sub-fertile bulls | [117] |
CMA3 | ||||
Human (n = 139) | IVF | %CMA3 positivity | %CMA3 positivity has negative correlation with farrowing rate %CMA3 positivity significant difference between fertilising and non-fertilising patients. | [118] |
Human (n = 30) | ICSI | %CMA3 | %CMA3 positivity showed significant negative correlation with FR | [119] |
Bulls (n = 12) (140 bulls ranked on embryo development rate, chose bottom 6 and top 6) | IVP | %CMA3 | Significant difference in %CMA3 between groups (p = 0.03), suggesting greater protamine deficiency in the high fertility group | [120] |
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Robertson, M.J.; Chambers, C.; Spanner, E.A.; de Graaf, S.P.; Rickard, J.P. The Assessment of Sperm DNA Integrity: Implications for Assisted Reproductive Technology Fertility Outcomes across Livestock Species. Biology 2024, 13, 539. https://doi.org/10.3390/biology13070539
Robertson MJ, Chambers C, Spanner EA, de Graaf SP, Rickard JP. The Assessment of Sperm DNA Integrity: Implications for Assisted Reproductive Technology Fertility Outcomes across Livestock Species. Biology. 2024; 13(7):539. https://doi.org/10.3390/biology13070539
Chicago/Turabian StyleRobertson, Maya J., Caitlin Chambers, Eloise A. Spanner, Simon P. de Graaf, and Jessica P. Rickard. 2024. "The Assessment of Sperm DNA Integrity: Implications for Assisted Reproductive Technology Fertility Outcomes across Livestock Species" Biology 13, no. 7: 539. https://doi.org/10.3390/biology13070539
APA StyleRobertson, M. J., Chambers, C., Spanner, E. A., de Graaf, S. P., & Rickard, J. P. (2024). The Assessment of Sperm DNA Integrity: Implications for Assisted Reproductive Technology Fertility Outcomes across Livestock Species. Biology, 13(7), 539. https://doi.org/10.3390/biology13070539