Seminal plasma from bulls with divergent plane of nutrition minimally alters bovine uterine endometrial epithelial cell gene expression in vitro

Abstract

Young beef bulls are often fed high-energy diets to maximize postweaning growth; however, overnutrition has been associated with decreased semen quality. Seminal plasma has been shown to prime the uterus for early pregnancy events in mammalian species; thus, alterations in this response caused by overnutrition could be detrimental or beneficial. The present study evaluated the impact of seminal plasma from bulls exposed to overnutrition on the transcriptome of endometrial epithelial cells in vitro. Yearling half-sibling beef bulls (n = 20) were stratified by age, body weight, and body condition score before being randomly assigned to one of two diets: 1) a diet formulated to elicit a target average daily gain (ADG) of 1.81 kg/d (High Gain, n = 10) or 2) a diet formulated to elicit a target ADG of 1.22 kg/d (Moderate Gain, n = 10). Seminal plasma was collected from each treatment group at three timepoints and then pooled and passed through a 22 μm sterile filter. Based on preliminary experiments, cells were randomly assigned to 1 of the 3 treatment groups: no treatment (Control), 1% seminal plasma from moderate gain bulls (Moderate Gain), or 1% seminal plasma from high gain bulls (High Gain) and cultured at 38.5 °C, 95% O₂, 5% CO₂ for 12 h. Experiments were conducted in duplicate per treatment, 3 times for a total of 6 experimental units per treatment group. Following the treatment period, total RNA was extracted from cells and underwent sequencing on the Illumina platform. Raw reads were mapped to the ARS-UCD1.3 Bos taurus RefSeq transcriptome, then converted to gene-level counts. The quasi-likelihood negative binomial generalized log-linear model (glmOL) from edgeR was used to test for significantly differentially expressed genes (DEG) at Benjamin-Hochberg adjusted (B.H. adj) P ≤ 0.05. There were 7,905 DEG (Padj ≤ 0.05) in bEND cells treated with seminal plasma from High Gain bulls compared with the Control. There were 8,933 (Padj ≤ 0.05) DEG in bEND cells treated with seminal plasma from Moderate Gain bulls compared with Control. There were 28 DEG (Padj ≤ 0.05) in bEND cells treated with seminal plasma from High Gain compared with Moderate Gain bulls. Metabolic pathways were depleted in each of these comparisons. In conclusion, seminal plasma alters the bEND cell transcriptome; however, the plane of nutrition had minimal effects.

Bull plane of nutrition minimally affects the endometrial transcriptomic response to seminal plasma in vitro

Introduction

The importance of seminal plasma in pregnancy and subsequent offspring health has been established in mice and swine, but minimally in cattle. Similar to other species, seminal plasma induces uterine inflammation in cattle (Howe and Black, 1963; Ibrahim et al., 2019). Dissimilar to other species, seminal plasma is not necessary for conception in cattle, nor does it improve conception rates, even in the context of assisted reproductive technologies where minimal seminal plasma is present (Odhiambo et al., 2009; Ortiz et al., 2019). Interestingly, mice that became pregnant without seminal plasma had offspring with poor neonatal growth, obesity, glucose intolerance, and hypertension (Bromfield et al., 2014). Seminal plasma uterine priming at estrus increased ipsilateral uterine artery resistance and reduced fetal embryo crown-rump length in cattle; however, only minor differences in birth morphometrics and postnatal liver transcriptomics were observed (Swanson et al., 2024). While the impact of seminal plasma priming may have minimal impacts on programming offspring, seminal plasma from over-conditioned bulls may alter the uterine immune cascade and subsequent events.

In mice, seminal plasma derived from males on a low-protein diet diminished the uterine immune response and offspring exhibited characteristics of metabolic dysfunction (Watkins et al., 2018). Vascular function and the renin-angiotensin system were impaired in these offspring and the subsequent generation (Morgan et al., 2020). In bulls exposed to overnutrition, the seminal plasma cytokine profile was altered (Harrison et al., 2023). While the effect of diet on seminal plasma-induced uterine inflammation is unknown in cattle, the inflammatory effect of seminal plasma on bovine endometrial epithelial (bEND) cells and uterine explants has been demonstrated by upregulated gene expression of pro-inflammatory cytokines (Ibrahim et al., 2019; Rizo et al., 2019). We hypothesize that seminal plasma will alter bEND cell transcriptomics, and seminal plasma from bulls with divergent rates of gain will show divergent bEND cell transcriptomics. Thus, our objective is to evaluate the effect of seminal plasma derived from moderate-gain and high gain bulls on bEND cell transcriptomics.

Materials and Methods

Animals and diets

All bulls were handled in accordance with procedures approved by the University of Georgia’s Institutional Animal Care and Use Committee (Animal Use Protocol # A2022 01-009-Y3-A0).

Experimental procedures to generate seminal plasma samples were performed at the University of Georgia’s Eatonton Beef Research Unit. Yearling, half-sibling Angus beef bulls (n = 20; body weight: 405.6 ± 44.03 kg; body condition score: 5.4 ± 0.5) were stratified by age, body weight, and body condition scores before being randomly assigned to 1 of the 2 treatments: 1) a diet formulated to induce an average daily gain (ADG) of 1.81 kg/d (High Gain, n = 10); or 2) a diet formulated to promote an ADG of 1.22 kg/d (Moderate Gain, n = 10). Bulls were housed in a feedlot facility equipped with a Smartfeed Pro (C-Lock Inc; Rapid City, SD) feed intake monitoring system that allowed individual feed intake monitoring. Similar dietary ingredients were utilized for both treatments; however, the rate of inclusion of each treatment varied to induce divergent rates of ADG. Diet composition is summarized in Supplementary Table 1. Bulls were exposed to their dietary treatment for a total of 114 d. Diet samples were collected every 2 wk and analyzed for nutritive value. Initial (day 0), day 36, day 76, and final (day 114) body weights were estimated based on 2 independent assessments within a 24 ± 4 h period. Moreover, body composition was evaluated using carcass ultrasonography (3.5 mHz linear array transducer, Aloka 500 V; Corimetrics Medical Systems Inc., Wallingford, CT, USA; Emenheiser et al., 2014) on the same days. Subcutaneous backfat, intramuscular fat, and longissimus dorsi area (LMA) were collected and then analyzed using Beef Information Analysis Pro Plus software (Designer Genes USA, Harrison, AR; Detweiler et al., 2019 ). Serial semen collections were performed using electroejaculation (Pulsator V, Lane Manufacturing Inc., Denver, CO) on days 109, 111, and 114.

Seminal plasma

Semen samples were evaluated for the presence of blood, urine, or any visual abnormalities before being processed for seminal plasma collection. Upon homogenizing the ejaculate, a 1.5-mL aliquot of whole semen was placed into a sterile microcentrifuge tube and centrifuged at 1,000 × g for 10 min at 20 °C to generate a cell-free seminal plasma supernatant. For each ejaculate, 0.5 to 1.0 mL of cell-free seminal plasma sample was transferred into a new sterile tube, snap frozen in liquid nitrogen, and immediately stored at −80 °C until shipment on dry ice to Mississippi State University (Mississippi State, MS). Upon arrival, semen was thawed and centrifuged at 2,500 × g for 10 min then seminal plasma from each treatment group was pooled and passed through a 22 μm sterile filter to ensure the absence of sperm cells. Seminal plasma was aliquoted and stored at −80 °C until use.

Cell subculture

Complete growth media components were purchased from American Type Culture Collection (ATCC; Manassas, VA) to make a 1:1 mixture of Ham’s F12 and Eagle’s Minimal Essential Medium with Earle’s BSS, 10% heat-inactivated fetal bovine serum, and 10% heat-inactivated horse serum. Growth media were incubator-acclimated prior to use throughout subculture. Incubator conditions were 37 °C, 95% O₂, 5% CO₂ per ATTC recommendations. Subsequent cell culture experiments were conducted at 38.5 °C, similar to normal bovine body temperature.

Two vials of bovine endometrial epithelial uterine cells (bEND; CRL-2398) were purchased from ATCC at passage 6 and sub-cultured, then stored in the vapor phase of liquid nitrogen at passages eight and ten following ATCC guidelines. In brief, vials were thawed in a 37 °C water bath for approximately 2 min, then suspended in 7 mL of 37 °C growth medium and centrifuged at 125 × g for 7 min. Media was then aspirated, and cells were resuspended in 15 mL of incubator-acclimated growth media, followed by culture in three 25 cm² flasks. Growth media was changed every 2 to 3 d. Cryopreservation was performed according to ATCC guidelines, and cells were stored in the vapor phase of liquid nitrogen.

Cell cytotoxicity and viability

Experiments were conducted to determine optimal seminal plasma inclusion in bEND cell experiments without causing cellular toxicity or reducing viability. Cell toxicity was evaluated using the CellTox Green Cytotoxicity Assay, and cell viability was evaluated using the CellTiter-Glo 2.0 Assay following manufacturer’s protocol (Promega, Madison, WI). These assays were multiplexed in triplicate on two 96-well clear bottom-white wall plates per day over 4 d (n = 24 per treatment). Treatments were 0%, 0.5%, 1%, 2.5%, and 5% seminal plasma. In brief, at ~85% confluence, seminal plasma and CellTox Green Dye (1 × final concentration) were added to growth media and incubated with bEND cells at 38.5 °C, 95% O², 5% CO² for 12 h. Following incubation, plates were equilibrated to room temperature for 10 min, orbital shaken for 1 min, and measured for fluorescence intensity at 485 nm excitation and 530 nm emission wavelengths. Then, CellTiter-Glo 2.0 Reagent was added, plates were shaken for 2 min, rested for 10 min, and then luminescence was measured. Fluorescence and luminescence were measured using the SpectraMax iD3 microplate reader (Molecular Devices, San Jose, CA).

Cell experiments

Cells were taken from frozen stock and subcultured to approximately 90% confluence in a 25 cm² flask, then expanded into six 25 cm² flasks and cultured until approximately 80% confluence. Flasks were randomly assigned to 1 of the 3 treatment groups: growth media only (Control), 1% seminal plasma from moderate gain bulls (Moderate Gain), or 1% seminal plasma from high gain bulls (High Gain) and cultured at 38.5 °C, 95% O₂, 5% CO₂ for 12 h. Following the treatment period, cells were visualized microscopically for any abnormalities, then removed from flasks using a cell scraper and centrifuged at 125 × g for 7 min, media was aspirated, and cells immediately underwent RNA extraction. Experiments were conducted in duplicate per treatment, 3 times for a total of 6 experimental units per treatment group. A new aliquot of cells from frozen stock was used on each day. Confluence at treatment, passage number at treatment, and day for each replicate are presented in Supplementary Table 2.

RNA extraction, sequencing, and differential gene expression

Total RNA was extracted from cells (n = 18) using the RNeasy mini kit (Qiagen, Hilden, Germany) according to the manufacturer’s protocol. Total RNA was quantified using a NanoDrop One spectrophotometer to ensure a total RNA amount ≥20 ng. Samples were stored −80 °C until shipment on dry ice for quality control using the 5,400 Bioanalyzer (Agilent, Santa Clara, CA), library construction, and Illumina paried-end 2 × 150 sequencing at Novogene Corporation (Sacramento, CA). RNA integrity number was ≥6.8 with an average of 8.4 across samples. Raw data is publicly available on NCBI (accession PRJNA1292269).

Differential gene expression analysis was conducted according to Swanson et al. (2024). In brief, raw data were mapped to the ARS-UCD1.3 Bos taurus RefSeq transcriptome from NCBI using salmon with the entire genome as decoy sequences (Patro et al., 2017). Transcript-level counts were converted to gene-level counts using tximport in R (Soneson et al., 2015). Gene-level counts were normalized using edgeR. Genes with low or incomplete expression (10 reads in at least 7 samples) were removed from further analysis (Bourgon et al., 2010). The quasi-likelihood negative binomial generalized log-linear model (glmQL) from edgeR was used to test for significantly differentially expressed genes at Benjamin-Hochberg adjusted (B.H. adj) P ≤ 0.05. Gene set enrichment analysis for both KEGG and GO databases was run using the Fry method from edgeR.

Statistical analysis

Statistical analyses for cell cytotoxicity and viability, and body weight and carcass composition were conducted using SAS 9.4 (SAS Institute, Cary, NC). Cell data were analyzed by ANOVA to determine the effects of seminal plasma inclusion on bEND cell cytotoxicity and viability in a completely randomized design where well was considered the experimental unit. Replicate and plate were included in the model as covariates. Animal data were analyzed by ANOVA for the effects of diet, day, and the diet × day interaction on body weight and composition in a completely randomized design using repeated measures, where bull was considered the experimental unit. Means were separated using Fisher’s least significant difference and data are presented as least square means ± standard error of the means. Statistical significance was considered at P ≤ 0.05.

Results

Bull body weight and composition

There was a diet × day interaction (P < 0.0001) for body weight, whereby body weights were increased in High Gain compared with Moderate Gain bulls on days 76 and 114 but not days 0 and 36 (Figure 1A). There was a diet × day interaction (P < 0.0001) for body condition scores, whereby body condition scores were increased in High Gain compared with Moderate Gain bulls on days 0, 76, and 114 but not day 36 (Figure 1B). There was a diet × day interaction (P < 0.0001) for 12th rib fat, whereby rib fat was increased in High Gain compared with Moderate Gain bulls on days 76 and 114 but not days 0 and 36 (Figure 1C). There was a diet × day interaction (P = 0.02) for intramuscular fat, whereby intramuscular fat was increased in High Gain compared with Moderate Gain bulls on days 76 and 114 but not days 0 and 36 (Figure 1D). There was a tendency (P = 0.06) for a diet × treatment interaction in longissimus dorsi muscle area, whereby it was increased in High Gain bulls compared with Moderate Gain on day 114 (Figure 1E).

Figure 1.

Impact of diet on bull body weights (A), body condition scores (B), 12th rib fat (C), intramuscular fat (D), and longissimus dorsi muscle area (E) throughout the feeding regimen. Bulls were fed to target either Moderate Gain (1.22 kg/d; n = 10) or High Gain (1.8 kg/d; n = 10). Data were collected on days 0, 36, 76, and 114 of dietary treatments. Data are presented as least square means ± standard error of the mean. ^*indicates differences between treatments within day at P ≤ 0.05. †indicates tendencies for differences between treatments within day at P ≤ 0.10.

Cell cytotoxicity and viability

Cell toxicity was increased (P < 0.0001) at 2.5%, and further increased at 5% seminal plasma, compared with 0%, 0.5%, and 1% inclusion (Figure 2A). Cell viability was decreased at 2.5%, and further decreased at 5% seminal plasma compared with 0%, 0.5%, and 1% inclusion (Figure 2B). Thus, the inclusion of seminal plasma at 1% of growth media was selected and used for further bEND cell experimentation.

Figure 2.

(A) Data are shown for cell cytotoxicity at increasing rates of seminal plasma inclusion, and (B) cell viability at increasing rates of seminal plasma. Seminal plasma is included as a percentage of complete growth media applied to wells (n = 24 wells per inclusion rate). Data are presented as lsmeans ± standard error of the mean. ^a,b,c,dDiffering superscripts indicate differences at P ≤ 0.01.

Gene differential expression

There were 4,129 genes downregulated (BH adj P ≤ 0.05), and 3,776 genes upregulated (BH adj P ≤ 0.05) in bEND cells treated with seminal plasma from High Gain bulls compared with Control. Genes upregulated (log2fold ≥ 2 and BH adj P ≤ 0.05) in bEND cells treated with seminal plasma from High Gain bulls include eukaryotic translation initiation factor 4E-like (LOC107131864), adipocyte differentiation-associated long noncoding RNA (ADNCR), FosB proto-oncogene, AP-1 transcription factor subunit (FOSB), uncharacterized LOC112449259, serum amyloid A3 (SAA3), uncharacterized LOC101905912, 2-oxoglutarate dehydrogenase mitochondria-like (LOC112446406; Table 1). Genes downregulated (log2fold ≤ − 2 and BH adj P ≤ 0.05) in bEND cells treated with seminal plasma from High Gain bulls include small integral membrane protein 20 (LOC101904614), thrombospondin type 1 domain containing 4 (THSD4), sarcoglycan delta (SGCD), uncharacterized LOC101908577, coagulation factor V (F5), aspartoacylase (ASPA), sodium voltage-gated channel alpha subunit 3 (SCN3A), cell adhesion molecule 3 (CADM3), neurotrophic receptor kinase 2 (NTRK2), histone deacetylase 9 (HDAC9), interleukin 18 receptor (IL18R1;Table 1).

Table 1.

Differential gene expression in bEND cells treated with seminal plasma from High Gain bulls compared with Control.

logFC	logCPM	F	P-value	FDR	Gene	Product
10.75	2.36	574.87	5.4E-14	5.0E-11	LOC107131864	eukaryotic translation initiation factor 4E pseudogene
5.84	3.79	130.23	1.2E-08	2.3E-07	ADNCR	adipocyte differentiation-associated long noncoding RNA
5.04	3.16	41.84	1.3E-05	6.8E-05	FOSB	FosB proto-oncogene, AP-1 transcription factor subunit, transcript variant X1
3.29	−0.50	8.51	1.1E-02	2.1E-02	LOC112449259	uncharacterized LOC112449259
3.15	0.10	135.77	4.4E-11	3.9E-09	SAA3	serum amyloid A 3
2.70	−1.92	23.83	6.4E-05	2.6E-04	LOC101905912	uncharacterized LOC101905912, transcript variant X1
2.06	4.34	64.02	1.0E-06	8.1E-06	LOC112446406	2-oxoglutarate dehydrogenase, mitochondrial-like
−8.51	−0.48	7.94	1.9E-02	3.6E-02	LOC101904614	small integral membrane protein 20
−3.15	−1.88	33.92	6.4E-06	3.7E-05	THSD4	thrombospondin type 1 domain containing 4
−2.37	−0.79	45.66	7.1E-07	6.0E-06	SGCD	sarcoglycan delta, transcript variant X1
−2.37	−1.99	17.93	3.2E-04	1.0E-03	LOC101908577	uncharacterized LOC101908577, transcript variant X3
−2.11	0.78	88.02	2.7E-09	7.7E-08	F5	coagulation factor V
−2.09	−1.68	16.31	5.2E-04	1.6E-03	ASPA	aspartoacylase, transcript variant X2
−2.08	2.42	100.17	6.0E-09	1.4E-07	SCN3A	sodium voltage-gated channel alpha subunit 3, transcript variant X2
−2.07	−2.05	15.71	6.2E-04	1.8E-03	CADM3	cell adhesion molecule 3, transcript variant X1
−2.04	−0.12	47.68	5.1E-07	4.6E-06	NTRK2	neurotrophic receptor tyrosine kinase 2, transcript variant X5
−2.04	−1.12	26.22	3.5E-05	1.6E-04	HDAC9	histone deacetylase 9, transcript variant X12
−2.01	2.80	110.99	2.8E-09	7.7E-08	IL18R1	interleukin 18 receptor 1, transcript variant X2

FDR = P-adjusted false discovery rate, logFC = log fold change at base, logCPM = log counts per million reads.

There were 4,549 genes downregulated (BH adj P ≤ 0.05), and 4,384 genes upregulated (BH adj P ≤ 0.05) in bEND cells treated with seminal plasma from Moderate Gain bulls compared with Control. Genes upregulated (log2fold ≥ 2 and BH adj P ≤ 0.05) in bEND cells treated with seminal plasma from Moderate Gain bulls include LOC107131864, ADNCR, FOSB, SAA3, uncharacterized LOC112449259, moderate density lipoprotein receptor class A domain containing 2 (LDLRAD2), LOC101905912, interstitial collagenase (LOC112444863), solute carrier family 16 member 4 (SLC16A4), C-K-C motif chemokine ligand 1 (GRO1), 2-oxoglutarate dehydrogenase, mitochondrial-like (LOC112446406), LOC104971009, LOC112449560, and LOC104974223 (Table 2). Genes downregulated (log2fold ≤ − 2 and BH adj P ≤ 0.05) in bEND cells treated with seminal plasma from Moderate Gain bulls include THSD4, CADM3, integrin subunit alpha 9 (ITGA9), EPH receptor A5 (EPHA5), HDAC9, vesicle amine transport 1like (VAT1L), tenascin C (TNC), F5, kelch like family member 13 (KLHL13), NTRK2, integrin subunit alpha 8 (ITGA8), SCN3A, myocardin (MYOCD), solute carrier family 14 member 1 (SLC14A1), adherens junctions associated protein 1, parvin beta (PARVB), calcium dependent secretion activator (CADPS), gremlin 1, DAN family BMP antagonist (GREM1), growth arrest specific 7 (Table 2).

Table 2.

Differential gene expression in bEND cells treated with seminal plasma from Moderate Gain bulls compared with Control.

logFC	logCPM	F	P-value	FDR	Gene	Product
11.02	2.36	647.15	2.1E-14	8.5E-12	LOC107131864	eukaryotic translation initiation factor 4E pseudogene
6.07	3.79	144.50	5.9E-09	7.3E-08	ADNCR	adipocyte differentiation-associated long noncoding RNA
4.09	3.16	25.32	1.7E-04	4.6E-04	FOSB	FosB proto-oncogene, AP-1 transcription factor subunit, transcript variant X1
3.15	0.10	137.00	4.1E-11	1.6E-09	SAA3	serum amyloid A 3
2.99	−0.50	6.68	2.1E-02	3.4E-02	LOC112449259	uncharacterized LOC112449259
2.63	−0.14	43.93	1.5E-06	7.0E-06	LDLRAD2	low density lipoprotein receptor class A domain containing 2, transcript variant X2
2.59	−1.92	22.06	1.0E-04	2.9E-04	LOC101905912	uncharacterized LOC101905912, transcript variant X1
2.45	−1.81	21.87	1.1E-04	3.0E-04	LOC112444863	uncharacterized LOC112444863
2.42	−1.67	11.29	3.1E-03	6.1E-03	SLC16A4	solute carrier family 16 member 4, transcript variant X6
2.20	4.29	201.44	8.9E-11	2.8E-09	GRO1	chemokine (C-X-C motif) ligand 1 (melanoma growth stimulating activity, alpha)
2.15	4.34	69.62	6.1E-07	3.3E-06	LOC112446406	2-oxoglutarate dehydrogenase, mitochondrial-like
2.05	−1.86	20.48	1.5E-04	4.2E-04	LOC104971009	uncharacterized LOC104971009
2.04	−1.70	16.36	5.1E-04	1.2E-03	LOC112449560	testis-specific serine/threonine-protein kinase 5-like
2.00	−1.45	23.51	6.9E-05	2.1E-04	LOC104974223	uncharacterized LOC104974223
−3.37	−1.88	36.12	4.1E-06	1.7E-05	THSD4	thrombospondin type 1 domain containing 4
−2.45	−2.05	20.35	1.6E-04	4.4E-04	CADM3	cell adhesion molecule 3, transcript variant X1
−2.44	−1.29	39.58	2.1E-06	9.5E-06	ITGA9	integrin subunit alpha 9
−2.36	−0.48	67.14	3.0E-08	2.7E-07	EPHA5	EPH receptor A5, transcript variant X2
−2.32	−1.12	33.12	7.6E-06	2.9E-05	HDAC9	histone deacetylase 9, transcript variant X12
−2.24	3.96	71.06	4.9E-07	2.7E-06	VAT1L	vesicle amine transport 1 like
−2.16	10.18	148.50	4.8E-09	6.2E-08	TNC	tenascin C, transcript variant X13
−2.13	0.78	92.11	1.8E-09	2.9E-08	F5	coagulation factor V
−2.11	−0.51	52.42	2.4E-07	1.5E-06	KLHL13	kelch like family member 13, transcript variant X5
−2.11	−0.12	51.09	2.9E-07	1.8E-06	NTRK2	neurotrophic receptor tyrosine kinase 2, transcript variant X5
−2.08	5.17	135.29	6.6E-09	8.0E-08	ITGA8	integrin subunit alpha 8
−2.06	2.42	101.68	5.3E-09	6.7E-08	SCN3A	sodium voltage-gated channel alpha subunit 3, transcript variant X2
−2.05	−0.79	42.98	1.1E-06	5.6E-06	MYOCD	myocardin, transcript variant X2
−2.03	1.09	98.33	9.8E-10	1.8E-08	SLC14A1	solute carrier family 14 member 1, transcript variant X7
−2.02	1.80	112.19	4.6E-10	1.0E-08	AJAP1	adherens junctions associated protein 1
−2.02	2.31	54.57	1.2E-06	5.8E-06	PARVB	parvin beta
−2.01	−1.50	22.26	9.6E-05	2.8E-04	CADPS	calcium dependent secretion activator, transcript variant X2
−2.01	6.42	75.32	4.1E-07	2.4E-06	GREM1	gremlin 1, DAN family BMP antagonist, transcript variant X1
−2.00	3.60	290.84	6.9E-14	1.8E-11	GAS7	growth arrest specific 7, transcript variant X3

FDR = P-adjusted false discovery rate, logFC = log fold change at base, logCPM = log counts per million reads.

There were 25 genes downregulated (BH adj P ≤ 0.05), and 3 upregulated (BH adj P ≤ 0.05) in bEND cells treated with seminal plasma from High Gain bulls compared with Moderate Gain (Table 3). Of these upregulated genes, none had a log2fold greater than 0.33, and of the downregulated genes, none were greater than −0.75. However, there are some genes of interest that were upregulated in cells treated with seminal plasma from High Gain compared with Control bulls.

Table 3.

Differential gene expression in bEND cells treated with seminal plasma from High Gain compared with Moderate Gain bulls.

logFC	logCPM	F	P-value	FDR	Gene	Product
0.33	3.65	22.62	8.74E-05	4.68E-02	FBXO32	F-box protein 32
0.26	8.45	31.32	1.11E-05	2.80E-02	VAT1	vesicle amine transport 1
0.24	5.23	20.50	1.54E-04	5.26E-02	POLR2M	RNA polymerase II subunit M, transcript variant X1
0.20	7.18	19.42	2.08E-04	5.26E-02	GOLM1	golgi membrane protein 1, transcript variant X4
0.19	5.39	20.95	1.36E-04	5.26E-02	AIDA	axin interactor, dorsalization associated
0.19	5.75	20.42	1.57E-04	5.26E-02	TRIM24	tripartite motif containing 24, transcript variant X3
0.18	7.26	20.84	1.40E-04	5.26E-02	MSRB3	methionine sulfoxide reductase B3, transcript variant X2
0.18	5.05	19.11	2.27E-04	5.45E-02	MVB12B	multivesicular body subunit 12B, transcript variant X4
0.17	7.62	21.14	1.29E-04	5.26E-02	FKBP9	FK506 binding protein 9
0.17	6.89	24.87	4.93E-05	3.99E-02	ITM2C	integral membrane protein 2C
0.16	10.78	21.88	1.06E-04	5.10E-02	QSOX1	quiescin sulfhydryl oxidase 1, transcript variant X1
0.15	8.65	21.75	1.10E-04	5.10E-02	CAST	calpastatin, transcript variant X1
0.14	7.63	21.19	1.28E-04	5.26E-02	NDRG1	N-myc downstream regulated 1, transcript variant X1
0.13	7.00	19.20	2.21E-04	5.45E-02	FLOT2	flotillin 2, transcript variant X2
0.17	7.50	22.16	9.85E-05	4.96E-02	HNRNPDL	heterogeneous nuclear ribonucleoprotein D like, transcript variant X3
−0.18	5.44	19.72	1.91E-04	5.26E-02	RBM23	RNA binding motif protein 23, transcript variant X5
−0.18	5.83	19.95	1.79E-04	5.26E-02	SLC7A6	solute carrier family 7 member 6, transcript variant X3
−0.18	6.70	19.07	2.30E-04	5.45E-02	TAOK2	TAO kinase 2, transcript variant X2
−0.19	5.59	26.12	3.63E-05	3.89E-02	NCAPH2	non-SMC condensin II complex subunit H2
−0.20	6.37	20.00	1.77E-04	5.26E-02	SLC52A2	solute carrier family 52 member 2, transcript variant X4
−0.20	9.01	24.49	5.41E-05	3.99E-02	ANKRD1	ankyrin repeat domain 1
−0.21	4.99	20.11	1.71E-04	5.26E-02	GALE	UDP-galactose-4-epimerase, transcript variant X3
−0.21	5.60	19.97	1.78E-04	5.26E-02	RUSC1	RUN and SH3 domain containing 1, transcript variant X5
−0.21	6.34	20.40	1.58E-04	5.26E-02	SRSF7	serine and arginine rich splicing factor 7, transcript variant X2
−0.22	4.22	22.11	9.98E-05	4.96E-02	MUS81	MUS81 structure-specific endonuclease subunit, transcript variant X2
−0.23	6.21	38.57	2.55E-06	1.92E-02	SLC8B1	solute carrier family 8 member B1, transcript variant X6
−0.24	5.63	22.95	8.02E-05	4.65E-02	TOP3A	DNA topoisomerase III alpha
−0.24	5.51	25.05	4.72E-05	3.99E-02	DGAT1	diacylglycerol O-acyltransferase 1, transcript variant X3
−0.25	5.83	19.77	1.92E-04	5.26E-02	ANO8	anoctamin 8, transcript variant X2
−0.25	5.01	19.05	2.31E-04	5.45E-02	MYO19	myosin XIX, transcript variant X3
−0.26	4.55	20.77	1.43E-04	5.26E-02	PPAN	peter pan homolog (Drosophila)
−0.26	5.11	29.72	1.58E-05	2.80E-02	SLC26A6	solute carrier family 26 member 6
−0.28	5.80	20.68	1.69E-04	5.26E-02	NEURL4	neuralized E3 ubiquitin protein ligase 4
−0.28	4.52	19.94	1.80E-04	5.26E-02	TONSL	tonsoku like, DNA repair protein
−0.28	5.64	23.81	6.85E-05	4.15E-02	ADCK5	aarF domain containing kinase 5, transcript variant X3
−0.29	5.66	24.16	6.28E-05	4.00E-02	SLC43A1	solute carrier family 43 member 1, transcript variant X10
−0.29	5.27	20.84	1.54E-04	5.26E-02	HSF4	heat shock transcription factor 4
−0.30	4.40	20.64	1.48E-04	5.26E-02	RAD54L	RAD54 like, transcript variant X2
−0.30	5.03	28.65	2.01E-05	2.80E-02	FANCG	Fanconi anemia complementation group G, transcript variant X4
−0.32	5.77	25.79	4.82E-05	3.99E-02	KHDC4	KH domain containing 4, pre-mRNA splicing factor, transcript variant X1
−0.32	5.21	28.93	1.90E-05	2.80E-02	CCNL1	cyclin L1, transcript variant X3
−0.33	6.65	35.50	5.88E-06	2.73E-02	SLC25A37	solute carrier family 25 member 37, transcript variant X1
−0.34	4.96	38.17	2.76E-06	1.92E-02	BRCA2	BRCA2, DNA repair associated, transcript variant X3
−0.35	3.70	23.88	6.32E-05	4.00E-02	TMC4	transmembrane channel like 4, transcript variant X1
−0.42	3.30	24.08	6.01E-05	4.00E-02	LOC104975559	uncharacterized LOC104975559, transcript variant X2
−0.43	3.24	28.14	2.26E-05	2.86E-02	PIDD1	p53-induced death domain protein 1, transcript variant X9
−0.43	3.03	29.55	1.64E-05	2.80E-02	ASB11	ankyrin repeat and SOCS box containing 11, transcript variant X1
−0.44	5.03	26.62	5.44E-05	3.99E-02	LIF	LIF, interleukin 6 family cytokine, transcript variant X2
−0.45	2.93	30.68	1.27E-05	2.80E-02	GSDMB	gasdermin B
−0.46	1.65	19.86	1.84E-04	5.26E-02	LOC112442547	uncharacterized LOC112442547, transcript variant X2
−0.47	5.20	29.94	2.95E-05	3.42E-02	WDR90	WD repeat domain 90, transcript variant X5
−0.47	4.12	20.76	2.03E-04	5.26E-02	LOC100847802	uncharacterized LOC100847802
−0.47	4.19	20.88	2.03E-04	5.26E-02	LOC100847818	uncharacterized LOC100847818
−0.47	4.11	26.94	3.95E-05	3.93E-02	LOC107131948	uncharacterized LOC107131948, transcript variant X2
−0.60	0.99	19.48	2.04E-04	5.26E-02	DPF1	double PHD fingers 1, transcript variant X5
−0.62	1.02	19.46	2.05E-04	5.26E-02	LOC112443181	uncharacterized LOC112443181
−0.69	2.10	32.52	8.58E-06	2.80E-02	CCDC136	coiled-coil domain containing 136, transcript variant X5
−0.71	1.67	20.59	1.50E-04	5.26E-02	LOC104972821	farnesyl pyrophosphate synthase pseudogene
−0.75	1.21	22.67	8.61E-05	4.68E-02	ATP2A1	ATPase sarcoplasmic/endoplasmic reticulum Ca2 + transporting 1, transcript variant X1

FDR = P-adjusted false discovery rate, logFC = log fold change at base, logCPM = log counts per million reads.

KEGG pathways

There were 240 pathways depleted (BH adj P ≤ 0.05) and 50 pathways enriched (BH adj P ≤ 0.05) in bEND cells treated with seminal plasma from High Gain bulls compared with Control. Pathways with greater than 200 genes that were depleted (BH adj P ≤ 0.05) in bEND cells treated with seminal plasma from High Gain bulls, compared with Control, include metabolic pathways, pathways in cancer, human papillomavirus infection, PI3K-AkT signaling pathway, MAPK signaling pathway, Salmonella infection, and endocytosis (Table 4). Pathways with greater than 200 genes that were enriched (BH adj P ≤ 0.05) in bEND cells treated with seminal plasma from High Gain bulls compared with Control include pathways of neurodegeneration (multiple diseases), Alzheimer disease, amyotrophic lateral sclerosis, herpes simplex virus 1 infection, Huntington disease, Parkinson disease, and prion disease (Table 4).

Table 4.

KEGG pathways depleted and enriched in bEND cells treated with seminal plasma from High Gain bulls compared with Control.

PathwayID	NGenes	Direction	P-value	FDR	P-value.Mixed	FDR.Mixed	Description
bta01100	1,177	Down	1.3E-01	1.5E-01	5.3E-13	1.6E-12	Metabolic pathways
bta05200	406	Down	4.9E-10	1.8E-08	1.4E-13	6.9E-13	Pathways in cancer
bta05165	265	Down	3.8E-10	1.8E-08	2.8E-13	1.0E-12	Human papillomavirus infection
bta04151	251	Down	1.5E-09	2.7E-08	2.7E-13	1.0E-12	PI3K-Akt signaling pathway
bta04010	229	Down	1.5E-08	8.5E-08	4.9E-13	1.5E-12	MAPK signaling pathway
bta05132	223	Down	1.1E-04	1.8E-04	3.0E-12	6.2E-12	Salmonella infection
bta04144	221	Down	2.9E-08	1.3E-07	1.7E-12	3.9E-12	Endocytosis
bta05022	393	Up	5.4E-05	9.1E-05	5.0E-12	9.2E-12	Pathways of neurodegeneration—multiple diseases
bta05010	330	Up	9.3E-04	1.3E-03	5.7E-12	1.0E-11	Alzheimer disease
bta05014	315	Up	1.1E-04	1.8E-04	1.8E-11	2.5E-11	Amyotrophic lateral sclerosis
bta05168	312	Up	5.3E-01	5.6E-01	4.3E-11	5.6E-11	Herpes simplex virus 1 infection
bta05016	263	Up	2.3E-06	4.8E-06	5.5E-11	6.9E-11	Huntington disease
bta05012	234	Up	4.6E-06	9.1E-06	7.3E-11	9.0E-11	Parkinson disease
bta05020	225	Up	3.0E-05	5.4E-05	5.4E-11	6.8E-11	Prion disease

FDR = P-adjusted false discovery rate, NGenes = number of genes up or down regulated in the pathway.

There were 260 pathways depleted (BH adj P ≤ 0.05) and 49 pathways enriched (BH adj P ≤ 0.05) in bEND cells treated with seminal plasma from Moderate Gain bulls compared with Control. Pathways with greater than 200 genes that were depleted (BH adj P ≤ 0.05) in bEND cells treated with seminal plasma from Moderate Gain bulls, compared with Control, include metabolic pathways, pathways in cancer, human papillomavirus infection, PI3K-Akt signaling pathway, Salmonella infection, and endocytosis (Table 5). Pathways with greater than 200 genes that were enriched (BH adj P ≤ 0.05) in bEND cells treated with seminal plasma from Moderate Gain bulls compared with Control include pathways of neurodegeneration (multiple diseases), Alzheimer disease, amyotrophic lateral sclerosis, herpes simplex virus 1 infection, Huntington disease, Parkinson disease, and Prion disease (Table 5).

Table 5.

KEGG pathways depleted and enriched in bEND cells treated with seminal plasma from Moderate Gain bulls compared with Control.

PathwayID	NGenes	Direction	P-value	FDR	P-value.Mixed	FDR.Mixed	Description
bta01100	1,177	Down	6.8E-03	8.2E-03	3.0E-13	1.0E-12	Metabolic pathways
bta05200	406	Down	1.6E-11	1.2E-09	1.5E-13	6.7E-13	Pathways in cancer
bta05165	265	Down	2.5E-11	1.2E-09	3.7E-13	1.1E-12	Human papillomavirus infection
bta04151	251	Down	8.7E-11	1.9E-09	2.1E-13	8.1E-13	PI3K-Akt signaling pathway
bta04010	229	Down	2.4E-09	1.0E-08	6.3E-13	1.7E-12	MAPK signaling pathway
bta05132	223	Down	1.1E-06	2.0E-06	2.6E-12	4.7E-12	Salmonella infection
bta04144	221	Down	5.5E-10	4.1E-09	1.3E-12	2.9E-12	Endocytosis
bta05022	393	Up	1.1E-04	1.6E-04	2.0E-12	4.0E-12	Pathways of neurodegeneration—multiple diseases
bta05010	330	Up	3.8E-03	4.8E-03	2.3E-12	4.3E-12	Alzheimer disease
bta05014	315	Up	9.1E-05	1.4E-04	8.6E-12	1.3E-11	Amyotrophic lateral sclerosis
bta05168	312	Up	1.2E-01	1.4E-01	1.6E-11	2.1E-11	Herpes simplex virus 1 infection
bta05016	263	Up	1.7E-06	3.1E-06	2.2E-11	2.7E-11	Huntington disease
bta05012	234	Up	4.4E-06	7.6E-06	2.4E-11	2.9E-11	Parkinson disease
bta05020	225	Up	2.8E-05	4.4E-05	1.7E-11	2.2E-11	Prion disease

FDR = P-adjusted false discovery rate, NGenes = number of genes up or down regulated in the pathway.

There were 4 pathways depleted (BH adj P ≤ 0.05) and 92 enriched (BH adj P ≤ 0.05) in bEND cells treated with seminal plasma from High Gain bulls compared with Moderate Gain. Pathways with greater than 200 genes that were depleted (BH adj P ≤ 0.05) in bEND cells treated with seminal plasma from High Gain bulls compared with Moderate Gain bulls include amyotrophic lateral sclerosis, herpes simplex virus 1 infection, Parkinson’s disease, and prion disease (Table 6). Pathways with greater than 200 genes that were enriched (BH adj P ≤ 0.05) in bEND cells treated with seminal plasma from High Gain bulls compared with Moderate Gain bulls include metabolic pathways, pathways in cancer, pathways of neurodegeneration (multiple diseases), Alzheimer disease, human papillomavirus infection, PI3K-Akt signaling pathway, MAPK signaling pathway, Salmonella infection, and endocytosis (Table 6).

Table 6.

KEGG pathways depleted and enriched in bEND cells treated with seminal plasma from High Gain bulls compared with Moderate Gain.

PathwayID	NGenes	Direction	P-Value	FDR	PValue.Mixed	FDR.Mixed	Description
bta05014	315	Down	9.2E-01	9.6E-01	2.2E-02	3.3E-02	Amyotrophic lateral sclerosis
bta05168	312	Down	3.2E-01	4.4E-01	1.8E-03	9.4E-03	Herpes simplex virus 1 infection
bta05012	234	Down	9.6E-01	9.7E-01	3.1E-02	4.3E-02	Parkinson disease
bta05020	225	Down	9.5E-01	9.6E-01	1.7E-02	2.8E-02	Prion disease
bta01100	1,177	Up	1.8E-01	2.9E-01	3.8E-03	1.3E-02	Metabolic pathways
bta05200	406	Up	1.8E-03	1.7E-02	8.0E-03	1.8E-02	Pathways in cancer
bta05022	393	Up	6.5E-01	7.4E-01	1.1E-02	2.2E-02	Pathways of neurodegeneration—multiple diseases
bta05010	330	Up	4.7E-01	5.9E-01	2.0E-02	3.1E-02	Alzheimer disease
bta05165	265	Up	4.6E-03	2.5E-02	7.7E-03	1.8E-02	Human papillomavirus infection
bta04151	251	Up	8.4E-03	3.6E-02	1.6E-02	2.7E-02	PI3K-Akt signaling pathway
bta04010	229	Up	6.0E-02	1.3E-01	3.8E-03	1.3E-02	MAPK signaling pathway
bta05132	223	Up	1.8E-02	5.5E-02	9.6E-03	2.1E-02	Salmonella infection
bta04144	221	Up	1.5E-03	1.6E-02	6.3E-03	1.6E-02	Endocytosis

FDR = P-adjusted false discovery rate, NGenes = number of genes up or down regulated in the pathway.

Gene ontology

There were 2,902 GO terms with depleted (BH adj P ≤ 0.05) genes, and 2,535 enriched GO terms (BH adj P ≤ 0.05) in bEND cells treated with seminal plasma from High Gain bulls compared with Control. There were 3,381 GO terms depleted (BH adj P ≤ 0.05), and 2,623 GO terms enriched (BH adj P ≤ 0.05) in bEND cells treated with seminal plasma from Moderate Gain bulls compared with Control. Enriched and depleted functions with greater than 200 genes are displayed in Table 7. Functions with greater than 200 genes that were depleted (BH adj P ≤ 0.05) in bEND cells treated with seminal plasma from High Gain bulls, compared with Control and Moderate Gain bulls compared with Control include integral components of membrane, plasma membrane, ATP binding, and endoplasmic reticulum membrane. Functions with greater than 200 genes that were enriched (BH adj P ≤ 0.05) in bEND cells treated with seminal plasma from High Gain bulls, compared with Control, include cytoplasm, nucleus, metal ion binding, nucleoplasm, and mitochondrion. Functions with greater than 200 genes that were enriched (BH adj P ≤ 0.05) in bEND cells treated with seminal plasma from Moderate Gain bulls, compared with Control, include nucleus, nucleoplasm, and mitochondrion.

Table 7.

Gene ontology functions

Contrast	GOID	Ngenes	Direction	P-Value	FDR	Ontology	Term
High gain vs control	GO:0016021	690	Down	6.2E-05	2.4E-04	Cellular component	integral component of membrane
High gain vs control	GO:0005886	356	Down	6.0E-06	3.7E-05	Cellular component	plasma membrane
High gain vs control	GO:0005524	346	Down	1.2E-05	6.3E-05	Molecular function	ATP binding
High gain vs control	GO:0005789	200	Down	5.0E-04	1.3E-03	Cellular component	endoplasmic reticulum membrane
High gain vs control	GO:0005737	800	Up	1.7E-02	2.8E-02	Cellular component	cytoplasm
High gain vs control	GO:0005634	767	Up	1.4E-03	3.2E-03	Cellular component	nucleus
High gain vs control	GO:0046872	491	Up	1.6E-02	2.7E-02	Molecular function	metal ion binding
High gain vs control	GO:0005654	371	Up	1.2E-04	4.1E-04	Cellular component	nucleoplasm
High gain vs control	GO:0005739	247	Up	1.7E-05	8.1E-05	Cellular component	mitochondrion
High gain vs moderate gain	GO:0005886	356	Up	6.2E-04	4.6E-02	Cellular component	plasma membrane
Moderate gain vs control	GO:0016021	690	Down	4.2E-07	2.9E-06	Cellular component	integral component of membrane
Moderate gain vs control	GO:0005886	356	Down	1.2E-08	2.1E-07	Cellular component	plasma membrane
Moderate gain vs control	GO:0005524	346	Down	3.7E-06	1.7E-05	Molecular function	ATP binding
Moderate gain vs control	GO:0005789	200	Down	2.0E-06	1.0E-05	Cellular component	endoplasmic reticulum membrane
Moderate gain vs control	GO:0005634	767	Up	5.0E-03	8.7E-03	Cellular component	nucleus
Moderate gain vs control	GO:0005654	371	Up	1.6E-04	4.2E-04	Cellular component	nucleoplasm
Moderate gain vs control	GO:0005739	247	Up	3.7E-05	1.2E-04	Cellular component	mitochondrion

FDR = P-adjusted false discovery rate, NGenes = number of genes up or down regulated in the pathway.

There were 21 GO terms depleted (BH adj P ≤ 0.05), and 135 enriched (BH adj P ≤ 0.05) in bEND cells treated with seminal plasma from High Gain bulls compared with Moderate Gain. The function with greater than 200 genes that were enriched (BH adj P ≤ 0.05) in bEND cells treated with seminal plasma from High Gain bulls compared with Moderate Gain is the plasma membrane.

Discussion

In this study, we show that seminal plasma does alter uterine epithelial endometrial cell gene expression, which helps to explain the complexities of seminal plasma uterine priming in beef cattle. Moreover, pathway analysis revealed seminal plasma from High Gain versus Control and Moderate Gain versus Control bulls had similar effects on cell gene expression, particularly in pathways involving the immune system. Together, these findings demonstrate seminal plasma alters uterine cell gene expression and likely function, but the divergent bull plane of nutrition seemingly has minimal impacts on this response.

Pathways that were depleted in bEND cells by High Gain seminal plasma compared with Control were also depleted by Moderate Gain seminal plasma compared with Control. These pathways have genes associated with cell proliferation, glycolysis, gluceoneogenesis, the TCA cycle, transcription, insulin-like growth factors, fibroblast growth factors, amino acid synthesis and metabolism, fatty acid synthesis, steroid hormone synthesis and receptors, and chemokine receptors. Surprisingly, these pathways also include genes associated with interleukins, tumor necrosis factor, nuclear factor-κ B, chemokine signaling, cytokines, oxidative stress, and apoptosis. Specifically, the downregulation of CADM3 and F5 by moderate and High Gain seminal plasma is surprising because of their roles in cell adhesion, a critical step in fetal-maternal attachment. In fact, Campos et al. (2018) showed CADM3 was upregulated in uterine endometrial tissue on day 15 of pregnancy. Similarly, Northrop-Albrecht et al. (2021) showed F5 was upregulated in endometrial tissue on day 16 of pregnancy in cows with greater pre-ovulatory circulating concentrations of estrogen, which has been attributed to improved embryo survival. Moreover, the downregulation of THSD4 and SCN3A by moderate and High Gain seminal plasma is interesting because of their roles in implantation, placenta development, and maternal recognition of pregnancy, respectively. In fact, THSD4 has been associated with positive pregnancy outcomes and bull fertility (Selvaraju et al., 2017; Pohler and Oliveira Filho, 2024). Also, Chaney et al. (2021) demonstrated SCN3A was upregulated by conceptus interferon in bovine uterine stromal cells. The downregulation of these specific genes and pathways is somewhat perplexing because of their roles in early pregnancy events, which has been shown to be supported by seminal plasma induced responses in mammals. Although bull dietary treatment does not appear to have negative or positive effects.

Pathways that were enriched by High Gain compared with Control were also enriched by Moderate Gain compared with Control. Interestingly, these pathways are all involved in neurodegenerative diseases among humans. These pathways have genes associated with reactive oxygen species, mitochondrial dysfunction, impairment of autophagy, ubiquitin-proteasome system disruption, mRNA biogenesis, calcium signaling, protein processing in the endoplasmic reticulum, NADH, cytochrome c, tyrosine metabolism, amino acid transporters, and heat shock proteins. Specifically, FOSB was upregulated in bEND cells by both Moderate and High Gain seminal plasma. The FOSB gene is involved in apoptosis of T cells, which have been demonstrated to increase prior to embryo implantation, indicating an important role of T cells in early pregnancy (Baumann et al., 2003; Robertson et al., 2013). Conversely, SAA3 was upregulated, which is unsurprising since it is associated with the regulation of tissue remodeling and innate immunity in epithelial cells, both of which have also been previously associated with seminal plasma uterine priming (Robertson, 2005; Weber et al., 2005). The upregulation of ADNCR by both Moderate and High Gain seminal plasma is interesting, although effects remain unclear in the present study, since it has been previously shown to play a role in intramuscular fat deposition (Wang et al., 2021). The upregulation of FOSB and SAA3 suggests that seminal plasma could have a positive effect on early pregnancy. Notably, in the Moderate Gain vs Control contrast, GRO1 was upregulated among cells treated with seminal plasma from Moderate Gain bulls, which has been shown to be a powerful embryokine in cattle (Tríbulo et al., 2018). This may be initial evidence suggesting a positive effect of moderate body weight gain among bulls on seminal plasma uterine priming.

When comparing cells treated with seminal plasma from Moderate Gain bulls with High Gain bulls, there is minimal evidence to suggest divergent gain alters the effects of seminal plasma on uterine endometrial epithelial cell gene expression. However, there were notable changes in KEGG pathways and GO terms associated with metabolic function and immunity. In particular, almost all pathways that were enriched in cells treated with High Gain seminal plasma are involved in mitochondrial dysfunction, NF-κB, MAPK, and p53 signaling. While seminal plasma has been widely demonstrated to cause a necessary inflammatory response in the uterus, mitochondrial dysfunction is likely detrimental to uterine priming and subsequent reproductive effects. Similarly, pathways that were depleted in cells treated with High Gain seminal plasma are involved in calcium signaling, mitophagy, and apoptosis. Calcium has been demonstrated to be an important factor for angiogenesis in endometrial cells during pregnancy (Bird et al., 2000; Gifford et al., 2003). Ultimately, this may suggest High Gain bull development strategies negatively impact seminal plasma uterine priming.

In conclusion, these data indicate that seminal plasma does affect bovine uterine endometrial epithelial cell gene expression in vitro. Although some genes that were downregulated were surprising since they have known positive effects on early pregnancy. Nevertheless, there were genes with known positive effects on early pregnancy upregulated by seminal plasma from both Moderate Gain and High Gain bulls. In addition, divergent planes of nutrition in young beef bulls do not appear to alter these effects, and as such, differing bull development strategies are not of concern in the present context. However, future research, including in vivo studies, are needed to fully understand the impact of bull nutritional management on seminal plasma and its effects on the uterus.

Glossary

Abbreviations

ADNCR

adipocyte differentiation-associated long noncoding RNA

AJAP1

adherens junctions associated protein 1

ASPA

aspartoacylase

ATCC

American Type Cell Culture

bEND

bovine endometrial epithelial cells

B.H. adj

Benjamin-Hochberg adjusted P-value

CADM3

cell adhesion molecule 3

CADPS

calcium dependent secretion activator

DEG

differential expressed genes

EPHA5

EPH receptor A5

F5

coagulation factor V

FOSB

FosB Proto-Oncogene, AP-1 Transcription Factor Subunit

GAS7

growth arrest specific 7

glmQL

quasi-likelihood negative binomial generalized log-linear model

GO

gene ontology term

GREM1

gremlin 1, DAN family BMP antagonist

GRO1

C-X-C Motif Chemokine Ligand 1

HDAC9

histone deacetylase 9

IL18R1

interleukin 18 receptor

ITGA8

integrin subunit alpha 8

ITGA9

integrin subunit alpha 9

KLHL13

kelch like family member 1

LDLRAD2

low density lipoprotein receptor class A domain containing 2

LOC101904614

small integral membrane protein 20

LOC101905912

uncharacterized LOC101905912

LOC101908577

uncharacterized LOC101908577

LOC104971009

uncharacterized LOC104971009

LOC104974223

uncharacterized LOC104974223

LOC107131864

eukaryotic translation initiation factor 4E-like

LOC112444863

interstitial collagenase

LOC112446406

2-oxoglutarate dehydrogenase, mitochondrial-like

LOC112449259

uncharacterized LOC112449259

LOC112449560

uncharacterized LOC112449560;

MYOCD

myocardin; N-myc downstream regulated 1, NDRG1

NTRK2

neurotrophic receptor kinase 2

PARVB

parvin beta

SAA3

serum amyloid A3

SCN3A

sodium voltage-gated channel alpha subunit 3

SGCD

sarcoglycan delta

SLC16A1

solute carrier family 16 member 1

SLC16A4

solute carrier family 16 member 4

THSD4

thrombospondin type 1 domain containing 4

TNC

tenascin C

VAT1L

vesicle amine transport 1like

Funding

This work was supported by USDA-AFRI Grants program (Animal Nutrition, Growth and Lactation, 2022-67015-36649) to PLPF. This publication is a contribution of the Mississippi Agricultural and Forestry Experiment Station. This material is based upon work that is supported in part by the National Institute of Food and Agriculture, U.S. Department of Agriculture, Hatch project under accession number 1011100. This research was supported in part by the U.S. Department of Agriculture, Agricultural Research Service, project 6066-31000-015-00D.

Conflict of Interest Statement

The authors have no conflicts of interest to declare.

Author Contributions

Rebecca M. Swanson (Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Validation, Visualization, Writing - original draft), Tony A. Arick (Data curation, Formal analysis, Resources, Software, Visualization, Writing - review & editing), L. M. Goncalves (Data curation, Investigation, Methodology, Project administration, Visualization, Writing - review & editing), Dylan Davis (Data curation, Investigation, Methodology, Project administration, Visualization, Writing - review & editing), R Stewart, Jr. (Data curation, Investigation, Methodology, Project administration, Visualization, Writing - review & editing), Pedro Fontes (Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing - review & editing), and Caleb Lemley (Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing - review & editing)