Mycotoxin ingestion during late gestation alters placentome structure,cotyledon transcriptome,and fetal development in pregnant sheep

Abstract

Ergot alkaloids, a class of mycotoxins, induce vasoconstriction when consumed by animals and humans. Pregnant ewes (n = 16; 81.2 kg ± 7.7) were assigned fed endophyte-infected tall fescue seed (E+; 4.14 μg ergovaline + ergovalinine/g seed) or a control diet (CON; 0 μg ergovaline + ergovalinine) for increasing duration during late gestation (from gd86 to gd110 or gd133) to examine changes in placentome morphology and mRNA transcriptome, and fetal development. Exposure to E+ fescue reduced serum prolactin concentrations at gd110 and gd133 demonstrating treatment efficacy. For control ewes, cotyledon and total placentome weights decreased with advancing gestation due to remodeling of placental tissues; however, cotyledon and placentome weight did not change with advancing gestation in E+ fed ewes. Fetal brain sparing was evident in E+ exposed fetuses at gd110 and gd133 compared to CON, which demonstrates asymmetrical growth and intrauterine growth restriction. Mycotoxin exposure (E+) resulted in differential expression of 22 genes in the cotyledon tissue at gd110 but only one gene at gd133 compared to CON. These results suggest that the response to mycotoxin exposure in the pregnant sheep model has an immediate impact on placental remodeling and fetal development that persists throughout the duration of the exposure period.

Keywords

Mycotoxin transcriptomics pregnancy

Introduction

Mycotoxin contamination of our food and feed supply are predicted to increase with global warming and climate change.¹ Ergot alkaloids, a class of mycotoxins, are found in endophyte-infected (E+) tall fescue that is the primary cool-season, perennial grass grazed by ruminant animals. Ergovaline, the most prevalent ergot alkaloid in tall fescue seed,² causes potent and widespread vasoconstriction³ and has been shown to constrict the umbilical and uterine arteries.^2,4,5 The biological activity of ergot alkaloids originates from their similarity to biogenic amines such as norepinephrine, serotonin, and dopamine and they exert their effect by working as an agonist on three primary receptors including the D₂ dopaminergic, α-2 adrenergic, and 5HT_2a serotonergic.^6–8 When consumed during gestation, ergot alkaloids induce placental insufficiency and intrauterine growth restriction (IUGR) most likely due to reduced uteroplacental blood flow.^9–11 These effects appear most detrimental during late gestation when placental remodeling and exponential fetal growth occurs.^5,12,13

In goats, ruminal infusion of E+ tall fescue seed extract induced vasoconstriction, as measured by luminal area of carotid artery using doppler ultrasound, by 2 d post dosing.¹⁴ The carotid luminal area was reduced by 46% with E+ extract infusion compared to baseline values.

Vasoconstriction can lead to hypoxia and reduced nutrient supply to the fetus. Hypoxia can alter fetal development but depends on duration of hypoxia event and stage of the developing fetus.¹⁵ In pregnant sheep, chronic hypoxia activates placental stress response and restricts fetal growth, which results in fetal brain-sparing.¹⁶ Research has shown that both hypoxia and oxidative stress are involved in intrauterine growth restriction (IUGR) in twin bearing ewes.¹⁷ However, little is known about how the duration of mycotoxin exposure during late gestation alters placental remodeling, nutrient transporters and fetal development. The pregnant sheep is an established model for human pregnancy and provides information on how mycotoxin exposure during pregnancy could impact placental and fetal development.¹⁸ It may be that the immediate insult of mycotoxin exposure to promote vasoconstriction is most detrimental to the developing placenta/fetus or that chronic exposure to mycotoxins results in reduced nutrient transport and growth retardation. Therefore, the objective of this study was to examine the effect of feeding endophyte-infected tall fescue seed containing ergot alkaloids to ewes at specific stages of late gestation (gd86 to gd110 or gd133) on placental structure, fetal development, and cotyledon mRNA transcriptome.

Materials and methods

Experimental design

All animal experimental procedures were reviewed and approved by the Clemson University Institutional Animal Care and Use Committee (AUP 2018-055). Mature ewes (n = 21; 81.2 kg ± 7.7) were randomly divided into 3 groups (n = 9/group) for estrous synchronization. Each week, one group of ewes was synchronized using an intravaginal controlled internal drug release (CIDR) insert (Eazi-Breed CIDR, Zoetis Animal Health) for 7 d. Upon CIDR removal, ewes were given prostaglandin F2α (12.5 mg i.m; Lutalyse; Pfizer, New York, NY) and turned in with a purebred Texel ram (Geneseek, Myostatin Muscled) fitted with a marking harness. Ewes were examined for pregnancy and lamb number using a transabdominal ultrasound between d 45 to 60 of gestation (BCF Easi-Scan Portable Ultrasound Machine, BCF Technology Ltd, Rochester, MN). Ewes estimated to be carrying twins (n = 16) were randomly assigned to endophyte-infected tall fescue seed (E+; 4.14 μg ergovaline + ergovalinine/g seed) or a control total mixed ration (CON; 0 μg ergovaline + ergovalinine). Ewes were individually fed ergot alkaloid treatments (E+ or CON) during specific stages of gestation (gd86 to gd110 or gd86 to gd133) in a 2 × 2 factorial. Fescue seed contains the highest concentrations of ergovaline/ergovalinine compared to the leaf blades or stems with sheaths.¹⁹ Fescue seed used in this study was analyzed for ergovaline and ergovalinine content.²⁰ All seed cultivars tested negative for ergotamine. Seed was fed to ewes at a total dose level of ergovaline/ergovalinine (E+ = 1.77 mg hd⁻¹ d⁻¹) per day starting on gd86. The dose level of ergovaline/ergovalinine fed in this study was based on previous research in which E+ seed was fed at a level of 0.8 mg/kg dry matter to induce vasocontriction.²⁰ To achieve this dose level, we individually fed ewes the same amount of dry matter intake each day containing the E+ seed at a quantity that equates to 0.8 mg/kg dry matter.¹² Nutrient analyses were performed on seed and TMR samples and rations were formulated to meet NRC requirements²¹ for late gestating ewes. Two ewes had to be removed from the study (1 CON and 1 E+, gd133) due to reduced intake and body weight gain that required veterinary attention.

Prolactin

Blood samples were collected from ewes on the terminal day of gestation according to treatment. Whole blood samples were collected by jugular venipuncture into serum collection tubes. Whole blood was allowed to clot for 30 min at room temperature, stored on i.e. and then serum was separated by centrifugation at 537 x g for 20 min at 4°C. Serum was stored at −20°C for future analysis. Serum prolactin concentrations were measured using a Prolactin ELISA kit (K040-H1; Arbor Assays, Ann Arbor, MI) with an average intra-assay variance was 3.16% and inter-assay variance was 5.92%. Samples were spiked with prolactin standards and the recovery was 92.4%.

Harvest and placentome collection

Ewes underwent a terminal necropsy at gd110 (n = 4/treatment) or gd133 (n = 3/treatment). The uterus was exposed through a mid-ventral incision and the full uterus was tied off, excised proximal to the cervix and weighed. A small incision was made in the uterine wall for the collection of fluid and removal of each fetus. The fetuses were removed from the sac and the umbilical cord was clamped and cut. Each fetus was towel dried, weighed, and brain weight obtained. After the removal of the fetuses, any remaining uterine fluid was drained. Placentomes were removed from the uterine wall and classified by type according to Vatnick et al²². . For RNA sequencing, type B placentomes were removed, cotyledon tissue separated from caruncle, and cotyledon was immediately frozen in liquid nitrogen. A sample of each available placentome type was collected for histology. The placentome was halved and stored in formalin until paraffin embedding. After remaining placentomes were typed and counted, the height, maximum diameter, and minimum diameter measurements were taken on each placentome. Then the cotyledon and caruncle from each placentome were carefully separated and weighed individually. Once placentomes were removed from the uterine wall, all membranes were removed, drained of any remaining fluid, and weighed collectively. The remaining empty uterus was cleaned and weighed.

Histology

Placentome samples were paraffin embedded using a Tissue-Tek VIP 6 AI Vacuum Infiltration Processor (Sakura Finetek USA, Inc, Torrance, CA). Samples were sectioned at 8 μm thickness using a microtome and stained immediately following sectioning. The H&E staining procedure was utilized in this study to evaluate placental histomorphology. For consistency, type B placentomes were imaged in brightfield using a Leica Microsystems (Buffalo Grove, Illinois) M205FCA stereomicroscope coupled with a Leica DMC4500 color camera. Images were collected using a 1.0X (Numerical aperture= 0.05) objective with digital zoom, for a final magnification of ×20. Using the Navigator feature in the Leica LAS-X software, images of the entire placentome were collected and stitched together; a shading correction was applied to achieve an even field of illumination. Measurements, including height, width, and area, of regions of tissue representative of Wharton’s jelly according to Stegeman²³ were performed using the area tracing tool in the Leica LAS-X software. To demonstrate the appearance of the Wharton’s jelly regions in detail, additional high magnification images of a subset of samples were collected using the same microscope at ×200 magnification with a ×5.0 (numerical aperture = 0.5) objective.

RNA sequencing

For consistency, type B placentomes were selected for RNA sequencing analysis. Total cellular RNA was isolated from cotyledon samples using Trizol reagent and purified using a PureLink Mini RNA kit (Invitrogen, Thermo Fisher Scientific, Waltham, MA) according to manufacturer instructions. RNA quantity was estimated using a NanoDrop 1000 Spectrophotometer (ThermoFisher). RNA quality was assessed using an Agilent 2100 Bioanalyzer (Agilent, Santa Clara, CA). All samples utilized for RNAseq has a RIN value of 8 or greater. Samples were submitted to the Clemson University Genomics and Bioinformatics Facility for RNAseq analysis. Total RNA was quantified using the Broad Range Assay in the Qubit (ThermoFisher Scientific, Waltham, MA). Library preparation was conducted using the NEB Next Ultra II Library Prep Kit for Illumina according to manufacturer instructions. Samples were sequenced to an average sequence depth of 51M reads using an Illumina NextSeq 550 sequencing platform at 150 bp paired-end reads. Raw sequencing data was transferred to the Clemson University Palmetto Cluster for analysis. Downsampling was conducted to ensure uniform coverage using seqtk v1.3-r106 (https://github.com/lh3/seqtk). FastQC v.0.11.8 was utilized to check sample quality (http://www.bioinformatics.babraham.ac.uk/projects/fastqc2010). All low-quality bases and adaptor sequences were trimmed using TrimGalore (v0.38).²⁴ After trimming, 99.6% of the remaining reads were aligned to the ovine reference genome (ftp://ftp.ensembl.org/pub/release-96/fasta/ovis_aries/) using GSNAP v2018-07-04.²⁵ Subread’s feature Counts v2.0.0 was used to count uniquely mapped reads that aligned to known genes in the ovine genome.²⁶ Gene counts were analyzed using edgeR v3.22.5.²⁷ Genes were considered differentially expressed if their false discovery rate (FDR) was <0.05 and their |log2FC| was greater than or equal to 1.0.

Gene ontology (GO) and KEGG pathway analysis

Differentially expressed genes were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis using clusterProfiler.²⁸

RT-qPCR validation

Gene expression analysis was conducted using quantitative real-time RT-PCR methods²⁹ to validate RNAseq results. Aliquots from the same RNA samples submitted for RNAseq were converted to cDNA using qScript cDNA SuperMix (Quanta Bio, Beverly, MA) according to manufacturer instructions. Real-time PCR was performed using a QuantStudio3 (Applied Biosystems, Thermo Fisher) and PowerUp (Applied Biosystems, Thermo Fisher) SYBR green according to the manufacturer’s directions. Genes for qPCR were selected based on having a published sequence in NCBI (https://www.ncbi.nlm.nih.gov/nucleotide/) and being differentially expressed by day and treatment. Primers for STARD (forward: GGGAACCTGTACAAAGGAGAAG; reverse: CATCCCACTGAGCTCGTAAAG) and GPR151 (forward: GATCTCAGCCAGGTGTTGATAG; reverse: GGCAACCTGCTCCAGTATT) were designed using PrimerQuest (Integrated DNA Technologies, IDT, Coralville, IA) and used to validate RNA-Seq results. The geometric mean of three housekeeping genes (glyceraldehyde 3-phosphate dehydrogenase, (GAPDH; forward: GGAGAAACCTGCCAAGTATGA; reverse: GCATCGAAGGTAGAAGAGTGAG), eukaryotic translation initiation factor 3 subunit K (EIF3K; forward: CTGACAGACAGCCAGCTAAA; reverse: CACGATGTTCTTGGGCTTAATG), and ubiquitously expressed prefoldin like chaperone (UXT; forward: CCACGGTTCTTACTAACACTTCT; reverse: TTGGCCAGCTCATATAC) was used for normalization. Normalized C_T values (ΔC_T = C_{T, gene} − C_{T, HK}) were calculated for each sample.³⁰ Relative gene expression was calculated using the ΔΔCT method and analyzed by ANOVA using GraphPad Prism (San Diego, CA).

Statistical analysis

Data were analyzed using a mixed procedure of SAS version 9.4 (SAS Institute Inc, Cary, NC) with fescue treatment (E+ vs CON), stage of gestation (gd110 or gd133) and two-way interaction in the model. Ewe was the experimental unit in this study. Statistical significance was declared at p < .05.

Results

Ewe body weight was greater (p < 0.05) at gd133 than gd110 but did not differ by fescue seed treatment (Table 1). Average daily gain and dry matter intake of ewes during late gestation did not differ by fescue seed treatment or stage of gestation. Dry matter intake was controlled in this study to reduce confounding of E+ fescue seed on nutrient intake and its relationship to fetal growth. Serum prolactin concentrations were lower (p < 0.05) for E+ than CON at gd110 and gd133.

Table 1.

Changes in ewe body weight, dry matter intake, and serum prolactin for ewes fed endophyte-infected (E+) tall fescue seed versus control (CON) at different stages of late gestation (gd110, gd133).

Gestation d	gd110		SEM	gd133		SEM
Fescue trt	CON	E+	SEM	CON	E+	SEM
n (Ewe)	4	4		3	3
Ewe body weight, kg	99.3^b	89.7^b	3.86	103.6^a	106.4^a	4.46
Average daily gain, kg/d	0.45	0.38	0.062	0.21	0.38	0.072
Dry matter intake, kg/d	2.70	2.56	0.098	2.45	2.68	0.113
Serum prolactin, pg/mL	4489.4^c	113.0^d	899.50	4059.7^c	55.8^d	1038.65

^abMeans in the same row with different superscripts differ (p < .05) by gestational day.

^cdMeans in the same row with different superscripts differ (p < .05) by fescue treatment.

Individual components of the full uterus are shown in Table 2. Weight of the empty uterus, amniotic fluid and membranes did not differ by fescue seed treatment or stage of gestation. There was an interaction between ergot alkaloid treatment and stage of gestation for cotyledon weight (fetal side of placentome). The weight of the cotyledon was lower (p < .05) for CON at gd133 than gd110 but did not change for E+ treatment. The weight of the caruncle (maternal side of the placentome) was lower (p < .05) at gd133 than gd110 but did not differ by fescue seed treatment. Total fetal weight was greater (p < .05) at gd133 than gd110 but did not differ by fescue seed treatment. Placentome number was not altered by ergot alkaloid treatment or state of gestation (Table 3). The majority of placentomes were type B (64.6% of total) and were not altered by stage of gestation or ergot alkaloid exposure. Placentome weight was greater (p < .05) for CON on gd110 than gd133; however, E+ treatment did not alter placentome weight by stage of gestation. Type B placentome weight accounted for the majority of total placentome weight in E+ at gd110 but at gd133 for CON. Placentome area was lower (p < 0.05) for CON at gd133 compared to CON at gd110 or E+ at either stage of gestation. These changes were related to increased area of type C and lower area of type B for E+ at gd133

Table 2.

Uterine components on a weight and percentage basis for ewes fed endophyte-infected (E+) tall fescue seed versus control (CON) at different stages of late gestation (gd110 or gd133).

Gestation d	gd110		SEM	gd133		SEM
Fescue trt	CON	E+	SEM	CON	E+	SEM
n (Ewe)	4	4		3	3
Empty uterus, g	830.2	750.6	119.80	945.4	1056.7	138.34
Membranes, g	517.7	317.8	64.20	474.1	536.8	74.14
Fluid, g	3290.2	2613.9	479.52	2848.9	2809.2	553.70
Placentome, g
Cotyledon	769.0^e	623.1^ef	65.57	444.7^f	665.1^ef	75.71
Caruncle	245.8^a	173.8a	24.14	121.6^a	133.2^a	27.87
Total fetal weight, g	4547.3^b	3549.4^b	900.09	7325.5^a	7068.5^a	10,039.33
Total, g	10,200.2	8028.6	1530.13	12,160.2	12,269.7	1766.84

^abMeans in the same row with different superscripts differ (p < .05) by gestational day.

^cdMeans in the same row with different superscripts differ (p < .05) by fescue treatment.

^efMeans in the same row with different superscripts differ (p < .05) by fescue treatment by gestational day interaction.

Table 3.

Placentome weight, number, and area by type for ewes fed endophyte-infected (E+) tall fescue seed versus control (CON) at different stages of late gestation (gd110, gd133).

Gestation d	gd110		SEM	gd133		SEM
Fescue trt	CON	E+	SEM	CON	E+	SEM
n (Ewe)	4	4		3	3
Placentome number	94.0	80.5	5.17	75.3	84.0	5.97
Type A, %	7.63	22.79	8.08	2.26	0	9.33
Type B, %	65.94	62.84	13.96	79.67	50.16	16.12
Type C, %	19.56	14.02	11.90	18.07	47.58	13.75
Type D, %	6.87	0.35	3.78	0	2.25	4.37
Placentome weight, g	1014.8^a	796.9^ab	77.32	566.3^b	798.3^ab	89.28
Type A, %	42.54	14.52	14.09	1.23	0	16.27
Type B, %	32.56^b	72.41^a	14.53	81.46^a	36.11^b	16.77
Type C, %	15.37	12.35	11.92	17.31	61.19	13.76
Type D, %	9.52	0.72	5.26	0	2.70	6.08
Placentome area, cm³	1268.0^a	1074.4^a	109.84	653.0^b	1108.8^a	126.83
Type A, %	21.64	13.83	12.52	2.17	0	14.46
Type B, %	50.36^ab	79.77^a	15.74	79.23^a	36.60^b	18.17
Type C, %	16.92^b	11.6^b	11.10	18.60^b	61.79^a	12.83
Type D, %	11.7	0.80	6.08	0	1.61	7.02

^abMeans in the same row with different superscripts differ (p < .05) by fescue treatment by gestational day interaction.

Changes in structure of the placentome were evaluated by histology and villi measurement were analyzed (Figure 1). Villi width was lower (p < .0001) at gd133 than gd110 but did not differ by ergot alkaloid treatment. The interaction between ergot alkaloid treatment and stage of gestation was significant (p < .05) for villi height and area of the placentome. Villi height and area were both greater (p < .05) for E+ than CON at gd110 but did not differ at gd133. Placental efficiency is calculated by relating the weight of the fetus to the cotyledon. Fetal to cotyledon weight was greater (p < .05) for CON than E+ at gd133 but did not differ between ergot alkaloid treatments at gd110 (Figure 2). Exposure to mycotoxins (E+) increased (p < 0.5) fetal brain to body weight ratio at both stages of gestation, which demonstrates asymmetrical growth and intrauterine growth restriction (IUGR) in lambs exposed to ergot alkaloids in utero.

Figure 1.

Placentome structure and fetal villi measurements for ewes fed endophyte-infected (E+) tall fescue seed compared to control diet (CON) at different stages of gestation (gd110 or gd133).

Figure 2.

The fetal to cotyledon weight (a) and brain to fetal body weight (b) ratios for ewes fed endophyte-infected (E+) tall fescue seed or control diet (CON).

Exposure to E+ mycotoxins differentially regulated (FDR <0.05) 22 genes with 15 down-regulated and 7 up-regulated genes at gd110 (Table 4). Many of the genes identified have unknown function in sheep and sequences are not annotated in the sheep genome (CCDC151, DSE, SLC35F1, C-C motif chemokine 2, MXRA5, RGS5, 5-hydroxytryptamine receptor 3C, SERPINA14, CYFIP2, USP13). StAR related lipid transfer domain containing 5 (STARD5) was up-regulated (FDR <0.05) in E+ compared to CON at gd110. In contrast, exposure to E+ mycotoxins at gd133 only differentially regulated one gene, G protein-coupled receptor 151 (GPR151). GPR151 was up-regulated (FDR <0.05) in E+ compared to CON at gd133. Gene expression analyses using qPCR for STARD and GPR151 was conducted to validate RNA sequencing results (Figure 3). Results from qPCR showed that STARD5 was up-regulated (p < .05) in E+ compared to CON at gd110. Relative expression of GPR151 was up-regulated (p < .05) in E+ compared to CON at gd133. The qPCR and RNA sequencing results are comparable for the two genes evaluated. No GO or KEGG pathway enrichment (p > .05) were detected.

Table 4.

Differentially expressed genes (FDR <0.05) in cotyledon tissue of ewes fed endophyte-infected (E+) tall fescue seed versus control (CON) by stage of gestation (gd86 to gd110 or gd86 to gd133).

	logFC	FDR	Gene name	Gene description
Down-regulated on gd110
ENSOARG00000018366	−3.808	1.37E-14	CCDC151	Coiled-coil domain containing 151
ENSOARG00000009347	−1.255	2.61E-04	DSE	Dermatan sulfate epimerase
ENSOARG00000008638	−4.484	1.04E-03	SLC35F1	Solute carrier family 35 member F1
ENSOARG00000009361	−3.670	1.47E-03		Novel
ENSOARG00000009627	−1.257	2.51E-03		C-cmotif chemokine 2
ENSOARG00000009554	−2.449	6.12E-03		Eotaxin
ENSOARG00000008760	−1.321	6.12E-03	MXRA5	Matrix remodeling associated 5
ENSOARG00000013470	−1.438	6.35E-03		Novel
ENSOARG00000011110	−1.905	8.46E-03	RGS5	Regulator ofG protein signaling 5
ENSOARG00000020625	−1.379	9.74E-03		5-Hydroxytryptamine receptor 3C
ENSOARG00000014971	−5.304	2.61E-02	SERPINA14	Serpin peptidase inhibitor, cladeA
ENSOARG00000009963	−1.824	2.76E-02		Serum amyloid a protein-like
ENSOARG00000017651	−2.094	3.88E-02		Myeloid-associated differentiation marker-like
ENSOARG00000011768	−0.952	4.74E-02	CYFIP2	Cytoplasmic FMR1 interacting protein 2
ENSOARG00000004021	−5.138	4.78E-02	Novel
Up-regulated on gd110
ENSOARG00000020687	1.432	4.91E-06		USP13 ubiquitin specific peptidase 13
ENSOARG00000008476	1.914	5.07E-03		Family with sequence similarity 184 member A
ENSOARG00000021083	1.112	1.25E-02	RPTN	Repetin
ENSOARG00000011133	2.179	1.25E-02	GPHA2	Glycoprotein hormone subunit alpha 2
ENSOARG00000007948	1.681	2.76E-02	HDDC2 HD	Domain containing 2
ENSOARG00000015807	1.709	3.53E-02	UNC13 A	Unc-13 homolog A
ENSOARG00000015778	1.238	4.78E-02	STARD5	StAR related lipid transfer domain containing 5
Up-regulated on gd133
ENSOARG00000014320	2.3023	2.59E-03	GPR151	G protein-coupled receptor 151

Figure 3.

Gene expression by qPCR of select genes for validation of sequencing project. (a). qPCR Gene Expression (b). StARD5 Pathway for Ovis aries (c). GPR151 Pathway for Ovis aries.

During late gestation (gd110 to gd133), 89 genes were differentially expressed with 45 up-regulated (FDR <0.05; logFC >1.5; Table 5) and 44 genes down-regulated (FDR <0.05; logFC < −1.5; Table 6). Vitelline membrane outer layer 1 homolog (VMO1), proline rich 7, synaptic (PRR7), surfactant protein D (DFTDP) and several novel genes were up-regulated (FDR <0.0002) from gd110 to gd133. Those genes that were down-regulated (FDR <0.001) genes included TET methylcytosine dioxygenase 1 (TET1), keratin 78 (KRT78), upstream transcription factor family member 3 (USF3), insulin-like growth factor binding protein 5 (IGFBP5), regulator of G protein signaling 5 (RGS5), and several novel genes. Gene ontology enrichment analysis identified many GO terms (qvalue <0.05) that corresponded with molecular function, cellular components and biological process (Table 7). KEGG Pathway enrichment was found for the up-regulation (qvalue <0.01; Table 8) of pathways associated with ribosome (oas03010), Coronavirus disease (oas05171), oxidative phosphorylation (oas00190), Parkinson’s disease (oas05012), pathways of neurodegeneration (oas05022), Alzheimer’s disease (oas05010), thermogenesis (oas04714), Huntington’s disease (oas05016), and non-alcoholic fatty liver disease (NAFLD; oas04932).

Table 5.

Differentially expressed genes (FDR <0.05; logFC >1.5) in cotyledon tissue of ewes from gd110 to gd133. Genes are displayed by level of significance.

No	Up-regulated	logFC	FDR	Gene	Gene description
1	ENSOARG00000024494	2.10	2.15E-07		Novel gene
2	ENSOARG00000007112	1.58	2.15E-07	VMO1	Vitelline membrane outer layer 1 homolog
3	ENSOARG00000005254	1.83	2.24E-05	PRR7	Proline rich 7, synaptic
4	ENSOARG00000011122	1.53	5.65E-05	CLEC3B	C-type lectin domain family 3 member B
5	ENSOARG00000010046	2.44	1.73E-04	SFTPD	Surfactant protein D
6	ENSOARG00000026301	1.67	1.77E-04		Novel gene
7	ENSOARG00000009256	1.62	2.08E-04	CD3G	CD3g molecule
8	ENSOARG00000017942	2.36	3.49E-04	CHGB	Chromogranin B
9	ENSOARG00000014064	1.60	5.37E-04		Novel gene
10	ENSOARG00000014416	2.07	6.81E-04		Novel gene
11	ENSOARG00000003297	1.64	1.48E-03	GABRP	Gamma-aminobutyric acid type a receptor subunit pi
12	ENSOARG00000021093	4.19	1.49E-03		Novel gene
13	ENSOARG00000014925	1.66	1.49E-03		Novel gene
14	ENSOARG00000002154	2.93	3.08E-03	SC5	Cathelin-related prepropeptide
15	ENSOARG00000002168	2.30	3.54E-03	OTOG	Otogelin
16	ENSOARG00000010869	1.55	5.20E-03	NPAS1	Neuronal PAS domain protein 1
17	ENSOARG00000018455	2.92	5.53E-03	OLFM3	Olfactomedin 3
18	ENSOARG00000004314	2.02	6.22E-03	G0S2	G0/G1 switch 2
19	ENSOARG00000018828	1.62	6.35E-03		Novel gene
20	ENSOARG00000002291	1.63	7.22E-03	RETN	Ovis aries resistin
21	ENSOARG00000004980	1.80	7.46E-03	MATN4	Matrilin 4
22	ENSOARG00000017718	3.10	7.87E-03	LOC101106834	Ubiquitin carboxyl-terminal hydrolase 17-like protein 6
23	ENSOARG00000003992	1.82	1.02E-02	SLC44A4	Solute carrier family 44 member 4
24	ENSOARG00000007979	1.78	1.09E-02		Novel gene
25	ENSOARG00000012583	1.51	1.22E-02	LHB	Luteinizing hormone beta polypeptide
26	ENSOARG00000020217	1.52	1.26E-02	SSTR3	Somatostatin receptor 3
27	ENSOARG00000022625	1.74	1.28E-02	Novel	Gene
28	ENSOARG00000009670	1.50	1.35E-02	CPXM2	Carboxypeptidase X, M14 family member 2
29	ENSOARG00000006280	1.79	1.83E-02	DLL3	Delta like canonical notch ligand 3
30	ENSOARG00000015039	1.97	1.84E-02		Novel gene
31	ENSOARG00000014243	1.68	2.03E-02	TNFSF13 TNF	Superfamily member 13
32	ENSOARG00000007572	1.76	2.10E-02	LOC101109142	Protein BEX2-like
33	ENSOARG00000002793	1.70	2.41E-02	LOC101119041	Cytochrome P450 4F22
34	ENSOARG00000026465	3.05	2.53E-02		Novel gene
35	ENSOARG00000018746	1.99	2.81E-02		Novel gene
36	ENSOARG00000018755	1.58	3.22E-02		Novel gene
37	ENSOARG00000015651	2.06	3.45E-02	DNAH8	Dynein axonemal heavy chain 8
38	ENSOARG00000001605	2.06	3.57E-02	LOC105607776	Cathelicidin-3-like
39	ENSOARG00000014461	2.58	3.71E-02	COL24A1	Collagen type XXIV alpha 1 chain
40	ENSOARG00000001843	2.11	3.78E-02		Novel gene
41	ENSOARG00000002487	1.75	4.52E-02	LOC101102967	Antigen WC1.1
42	ENSOARG00000009954	1.77	4.56E-02		Novel gene
43	ENSOARG00000008883	1.53	4.77E-02	LOC101108075	Interferon-inducible GTPase 5-like
44	ENSOARG00000006196	1.79	4.77E-02		Novel gene
45	ENSOARG00000005238	1.53	4.96E-02	ENO2	Enolase 2

Table 6.

Differentially expressed genes (FDR <0.05; logFC < −1.5) in cotyledon tissue of ewes from gd110 to gd133. Genes are displayed by level of significance.

No	Down-regulated	logFC	FDR	Gene	Gene Description
1	ENSOARG00000000075	−1.65	5.05E-07	Novel gene
2	ENSOARG00000005141	−1.75	6.41E-07	TET1	Tet methylcytosine dioxygenase 1
3	ENSOARG00000013090	−2.34	7.22E-06		Novel gene
4	ENSOARG00000016800	−3.08	2.13E-05	KRT78	Keratin 78
5	ENSOARG00000014835	−1.64	2.28E-05		Novel gene
6	ENSOARG00000022274	−4.08	2.28E-05		Novel gene
7	ENSOARG00000019468	−1.59	2.08E-04	USF3	Upstream transcription factor family member 3
8	ENSOARG00000000724	2.70	5.03E-04		Novel gene
9	ENSOARG00000019421	−1.83	6.71E-04	IGFBP5	Insulin like growth factor binding protein 5
10	ENSOARG00000011110	−2.01	9.26E-04	RGS5	Regulator of G protein signaling 5
11	ENSOARG00000014971	−4.62	1.31E-03	SERPINA14	Serpin peptidase inhibitor, clade A
12	ENSOARG00000001637	−1.86	1.76E-03	FMOD	Fibromodulin
13	ENSOARG00000010036	−1.58	1.81E-03	HHIP	Hedgehog interacting protein
14	ENSOARG00000003707	−1.61	2.32E-03		Novel gene
15	ENSOARG00000023081	−2.01	2.51E-03		Novel gene
16	ENSOARG00000004021	−4.21	2.60E-03		Novel gene
17	ENSOARG00000026230	−2.14	2.98E-03		Novel gene
18	ENSOARG00000025441	−1.67	3.00E-03		Novel gene
19	ENSOARG00000006710	−3.16	3.00E-03	OLFM4	Olfactomedin 4
20	ENSOARG00000005969	−1.56	3.60E-03		Novel gene
21	ENSOARG00000000980	−1.51	4.23E-03		Novel gene
22	ENSOARG00000009361	−3.46	5.12E-03		Novel gene
23	ENSOARG00000004785	−1.70	5.30E-03	PIK3CG	Phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit gamma
24	ENSOARG00000024878	−1.58	6.62E-03		Novel gene
25	ENSOARG00000017565	−1.88	8.54E-03	TRPC5	Transient receptor potential cation channel subfamily C member 5
26	ENSOARG00000018256	−1.52	9.28E-03	DMD	Dystrophin
27	ENSOARG00000010658	−2.32	1.37E-02		Novel gene
28	ENSOARG00000023116	−1.58	1.39E-02		Novel gene
29	ENSOARG00000020589	−1.59	1.53E-02	SPHKAP	SPHK1 interactor, AKAP domain containing
30	ENSOARG00000001879	−1.75	1.63E-02		Novel gene
31	ENSOARG00000021045	−1.92	2.23E-02	GATM	Glycine amidinotransferase
32	ENSOARG00000012607	−1.52	2.34E-02		Novel gene
33	ENSOARG00000006872	−1.52	2.38E-02	HOXB9	Homeobox B9
34	ENSOARG00000017968	−1.56	2.41E-02		Novel gene
35	ENSOARG00000006128	−1.74	2.41E-02	RNF125 ring finger protein 125
36	ENSOARG00000017842	−1.51	2.54E-02	RTL9 retrotransposon Gag like 9
37	ENSOARG00000002802	−2.02	2.86E-02	DIO2 iodothyronine deiodinase 2
38	ENSOARG00000025649	−2.07	2.88E-02		Novel gene
39	ENSOARG0000002536	−1.79	3.17E-02		Novel gene
40	ENSOARG0000001447	−2.17	3.26E-02	ZP2 zona	Pellucida glycoprotein 2
41	ENSOARG00000009762	−1.95	3.30E-02	LOC101106610	Dihydrodiol dehydrogenase 3-like
42	ENSOARG00000001192	−1.74	3.42E-02		Novel gene
43	ENSOARG00000014819	−1.57	4.52E-02	LOC101116002	Calcium-activated chloride channel regulator 1-like
44	ENSOARG00000012671	−1.87	4.75E-02	LOC101113761	Ribonuclease pancreatic

Table 7.

Gene ontology enrichment of differentially expressed genes in cotyledon tissue of ewes by stage of gestation (gd110 to gd133).

GO Terms	Ontology	Description	qvalues
GO:0003735	MF	Structural constituent of ribosome	3.66E-15
GO:0005840	CC	Ribosome	3.66E-15
GO:0005198	MF	Structural molecule activity	2.18E-09
GO:0006518	BP	Peptide metabolic process	3.96E-09
GO:0044391	CC	Ribosomal subunit	5.75E-09
GO:0006412	BP	Translation	1.22E-08
GO:0043603	BP	Cellular amide metabolic process	1.50E-08
GO:0043043	BP	Peptide biosynthetic process	2.50E-08
GO:0043604	BP	Amide biosynthetic process	1.29E-07
GO:1990904	CC	Ribonucleoprotein complex	7.49E-07
GO:0005739	CC	Mitochondrion	1.39E-06
GO:1901566	BP	Organonitrogen compound biosynthetic process	6.52E-05
GO:0015934	CC	Large ribosomal subunit	1.05E-04
GO:0019866	CC	Organelle inner membrane	5.09E-04
GO:0005743	CC	Mitochondrial inner membrane	9.39E-04
GO:0000003	BP	Reproduction	1.02E-03
GO:0022414	BP	Reproductive process	1.02E-03
GO:0005740	CC	Mitochondrial envelope	1.34E-03
GO:0098798	CC	Mitochondrial protein-containing complex	1.43E-03
GO:0031966	CC	Mitochondrial membrane	4.09E-03
GO:0008509	MF	Anion transmembrane transporter activity	6.12E-03
GO:0031967	CC	Organelle envelope	7.98E-03
GO:0031975	CC	Envelope	7.98E-03
GO:0044703	BP	Multi-organism reproductive process	9.92E-03
GO:0050794	BP	Regulation of cellular process	1.16E-02
GO:0016773	MF	Phosphotransferase activity, alcohol group as acceptor	1.17E-02
GO:0050789	BP	Regulation of biological process	1.17E-02
GO:0016301	MF	Kinase activity	1.48E-02
GO:0051704	BP	Multi-organism process	1.50E-02
GO:0043565	MF	Sequence-specific DNA binding	1.84E-02
GO:0065007	BP	Biological regulation	1.84E-02
GO:0003677	MF	DNA binding	1.88E-02
GO:0140096	MF	Catalytic activity, acting on a protein	2.22E-02
GO:0005524	MF	ATP binding	2.40E-02
GO:0030554	MF	Adenyl nucleotide binding	2.40E-02
GO:0032559	MF	Adenyl ribonucleotide binding	2.40E-02
GO:0004672	MF	Protein kinase activity	2.68E-02
GO:0048732	BP	Gland development	2.68E-02
GO:0036094	MF	Small molecule binding	3.45E-02
GO:0000976	MF	Transcription regulatory region sequence-specific DNA binding3.69E-02
GO:0000166	MF	Nucleotide binding	3.94E-02
GO:1901265	MF	Nucleoside phosphate binding	3.94E-02
GO:0001067	MF	Regulatory region nucleic acid binding	4.15E-02
GO:0007264	BP	Small GTPase mediated signal transduction	4.15E-02

Table 8.

KEGG enrichment of differentially expressed genes in cotyledon tissue of ewes by stage of gestation (gd110 to gd133).

ID	Description	Qvalues
oas03010	Ribosome	1.67E-27
oas05171	Coronavirus disease - COVID-19	1.41E-16
oas00190	Oxidative phosphorylation	2.53E-04
oas05012	Parkinson disease	2.09E-03
oas05022	Pathways of neurodegeneration - multiple diseases	3.54E-03
oas03040	Spliceosome	3.54E-03
oas05020	Prion disease	5.06E-03
oas05010	Alzheimer disease	8.71E-03
oas04714	Thermogenesis	8.71E-03
oas05016	Huntington disease	1.02E-02
oas04932	Non-alcoholic fatty liver disease	1.02E-02
oas04723	Retrograde endocannabinoid signaling	2.75E-02
oas00310	Lysine degradation	3.05E-02
oas05415	Diabetic cardiomyopathy	3.26E-02
oas04260	Cardiac muscle contraction	3.89E-02

Discussion

Ergot alkaloids, a class of mycotoxins, are present in endophyte-infected tall fescue (E+) and consumption by ruminants (cattle, sheep, goats) induces vasoconstriction which reduces blood flow.⁷ Limited research has examined how these mycotoxins alter placental and fetal development during gestation. Previous research found that exposure to ergot alkaloids during late gestation (gd86 to gd133) had the greatest impact on placental remodeling,^13,29,31 fetal development¹⁰ and subsequent postnatal growth³²; however, how these changes occur within this stage of gestation have not been examined. In this study, ergot alkaloid intake for E+ ewes was maintained by feeding tall fescue seed with known levels throughout late gestation. Feed intake was similar between treatments to reduce confounding of intake reduction by E+ exposure and its relationship to fetal growth. The diets, E+ and CON, were formulated to be isonitrogenous and isocaloric, and fed at amount to meet the requirements for pregnant ewes with twins during late gestation. Ergot alkaloid consumption (E+) reduced serum prolactin concentrations at gd110 by 29.6-fold and gd133 by 71.8-fold compared to controls. Reductions in serum prolactin levels are commonly reported in sheep grazing endophyte-infected tall fescue pastures^33–35 or fed E+ tall fescue seed containing ergot alkaloids.^11,31,36 The reductions in prolactin concentrations are caused by the structural similarity of the ergoline ring of ergot alkaloids to dopamine, which allows them to interact with D2 dopamine receptors.⁷

During late gestation, placenta growth plateaus around gd80³⁷ to gd90³⁸ and then remodeling of the placenta occurs.³⁹ The ovine placenta experiences a period of rapid growth in which the fetal villi invade the maternal stroma of the caruncle .^23,39,40 The fetal villi consist of a trophoblast layer that contains large regions ofamorphous connective tissue like Wharton’s jelly.^23,39 As maternal vascular beds develop, the amorphous connective tissue disappears, and only thin strands remain. The decrease in weight of the cotyledon over time is related to this loss of connective tissue which contains a high amount of water. These changes were evident in control ewes were cotyledon and total placentome weights decreased at gd133 compared to gd110; however, cotyledon weight did not change by stage of gestation in E+ fed ewes. Placentome area was also lower at gd133 in control compared to gd110 but did not change in E+. Ewes fed E+ fescue seed also had greater placentome villi height and area than controls at gd110 or gd133 regardless of fescue treatment. These results suggest that E+ exposure slows the process of placental remodeling wherein maternal capillary beds replace large regions of amorphous connective tissue to facilitate nutrient exchange to the fetus. Britt et al.¹³ identified greater amorphous connective tissue within the fetal villi from mycotoxin exposure that indicates underdeveloped maternal vascular beds that may hinder fetal growth.

The progression of placentome morphology has been extensively investigated but continues to draw mixed results. It is hypothesized that placentome morphology may shift towards more advanced type C and D placentomes during late gestation when the fetal demand for nutrients is at its highest; especially in cases of insufficient uterine environments such as undernutrition and hypoxia.^41–44 Osgerby et al.⁴² speculated that flattening of the placentome, which occurs in advancement, may be associated with attempts to increase nutrient delivery to the fetus. However, morphology is not always altered in cases of adverse intrauterine conditions.⁴⁵ In this study, ewes fed E+ fescue seed had a shift in placentome area to type C instead of type B at gd133. Placental efficiency, as defined by the ratio of fetal weight to placental weight, is indicative of how well the placenta adapts to meet the high nutrient demand for fetal growth.⁴⁶ In this study, ewes fed E+ seed had 30% less fetus per gram of cotyledonary tissue compared to controls at gd133. Prolonged exposure to E+ fescue seed appears to lower placental efficiency as indicated by a lower fetal:cotyledon weight ratio at gd133.

During late gestation, exponential fetal growth begins with over 80% of fetal weight obtained during this time.^38,47 Previous research found that exposure to E+ fescue during late gestation reduced fetal BW at gd133 by 15%¹¹ and birth weight by 10.2%.³¹ Brain to fetal body weight was increased with exposure to mycotoxins in this study, which is an indicator of asymmetrical growth and IUGR.^15–17 This agrees with our earlier work that showed asymmetrical growth in lambs at gd133¹⁰ after exposure to mycotoxins during late gestation that altered growth of the offspring and delayed puberty in females.³² The asymmetrical growth was already established at gd110 and remained at gd133. These results suggest that ergot alkaloid exposure during this stage of gestation (gd86 to gd110) or that the immediate insult of ergot alkaloids (first 25 d on E+ treatment) is having the greatest impact on fetal growth and IUGR. Others have reported long-term consequences of offspring that were born to nutrient restricted dams.^48–50

Exposure to ergot alkaloids differentially expressed 22 genes in cotelydon tissue at gd133 and 1 gene at gd133. Most the genes identified have an unknown role in placental and fetal development in the sheep but have been identified to be associated with hypertension and placental insufficiency in other species. Jerber et al.⁵¹ discusses that CCDC151 is involved in cilia function but also may have additional roles in non-motile function including cell polarity and mitotic spindle orientation for vertebrates. Regulator of G protein signaling 5 (RGS5) gene regulates hemodynamic adaptation to pregnancy and loss of RGS5 causes gestational hypertension in the mouse.⁵² Goyal et al.⁵³ reported that RGS5 was down regulated in a rat model of placental insufficiency. Other genes (SERPINA14 and STARD5) appear to be related to hormone and lipid metabolism. SERPINA14 plays a role as an immune regulator and mediates progesterone’s immunosuppressive response in the sheep.⁵⁴ The STARD5 gene is known to bind to cholesterol and 25-hydroxycholesterol to help with interchange of lipids between membranes.⁵⁵ In mice, STARD5 responds to stress and adjusts intracellular cholesterol homeostasis.⁵⁶ Fescue toxicosis has been shown to reduce plasma cholesterol levels in grazing cattle.⁵⁷ Edwards et al.⁵⁸ reported that nutrient restriction from gd35 to gd125 up-regulated GPR151 in placentomes from ewes that produced non-IUGR fetuses compared to IUGR fetuses. No differences in gene ontology or KEGG pathway analysis were noted for E+ compared to CON at gd110 or gd133. Previous research identified four genes (LECT2, SLC22A9, APOC3, MBL2) that were differentially expressed in the cotyledon from ewes fed E+ fescue from gd36 to gd133 and clusters associated with nutrient transport and cellular metabolism.²⁹ These differences in response to fescue may be related to the duration of exposure to ergot alkaloids with this short-term study having less impact on mRNA expression compared to long-term exposure.

From gd110 to gd133, 89 genes were differentially expressed (FDR <0.05; log2FoldChange < −1.5 or >1.5) in the cotyledon tissues. Many of these genes have associated roles with immune response and insulin action. CLEC3B was identified in bovine where it was up-regulated in pregnant versus non-pregnant heifers and appears to be involved in immune response to IFN-τ.⁵⁹ SFTPD has been shown to be an integral component of female reproductive tract and appears involved in immune response.⁶⁰ Others ⁴² have also observed decreased expression of IGFBP5 mRNA in the placentome of sheep from gd90 to 135. Jia et al.⁶¹ proposed that IGFBP5 may be used as a marker for preeclampsia in humans because of its high expression in the preeclamptic placenta. RGS5 is reported to play a role in cardiovascular function during pregnancy⁶² and serves as a marker for gestational hypertension in humans⁶³

Gene ontology analysis discovered enrichment of molecular function, cellular component, and biological process during gestation from gd110 to 133. KEGG pathway enrichment was found for pathways associated with ribosome, oxidative phosphorylation, splicesome, thermogenesis, and many disease states. Upon further investigation with KEGG pathways analysis using KEGG Mapper, oxidative phosphorylation is the primary driver between the overlap with disease states (Huntington’s disease, Parkinson’s disease, Alzheimer’s disease, and NAFLD) as well as several cancer pathways. In all mammals, placental energy demand is met primarily by oxidative phosphorylation.⁶⁴ This shows a comprehensive up-regulation of genes associated with ribosomal function. Research suggests the rate of rRNA transcription is tightly linked to ribosome biogenesis, which regulates cell growth and proliferation.⁶⁵

Exposure to E+ fescue at specific stages during late gestation show reduced serum prolactin concentration and slowed placental remodeling which resulted in placental inefficiency and asymmetrical growth of the fetus that was evident by gd110 and continued to gd133. Transcriptomic changes in the cotyledon tissue of E+ were identified but most of the genes identified have an unknown role and further research is needed to determine their involvement in placental remodeling and mycotoxin exposure. These results suggest that the response to mycotoxin exposure in the pregnant sheep model has an immediate impact on placental remodeling and fetal development that persists throughout the duration of the exposure period.

Footnotes

Author contributions

SKD, JLK and JLB designed the research project and wrote the manuscript. JLB, MAG and SMJ conducted the animal experiment, sample collection and sample preparation. JLB and REN analyzed the RNA Seq data. RRP and TFB conducted the histology image analyses. All authors have read and approved the manuscript.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Technical Contribution No. 6801 of the Clemson University Experiment Station. This material is based upon work supported by NIFA/USDA, under project number 1700537. The Leica stereoscope used in this study is housed in the Clemson Light Imaging Facility and was purchased with funds from the Clemson University Division of Research.

Data availability statement

The datasets generated and analyzed during the current study are available in Gene Expression Omnibus (GEO) repository (wlalwaggtjyhlqj).

ORCID iDs

RE Noorai

SK Duckett

References

Liu

Van der Fels-Klerx

. Quantitative modeling of climate change impacts on mycotoxins in cereals: a review. Toxins 2021; 13(4): 276. https://www.narcis.nl/publication/RecordID/oai:library.wur.nl:wurpubs%2F582896. DOI: 10.3390/toxins13040276.

Lyons

Plattner

Bacon

. Occurrence of peptide and clavine ergot alkaloids in tall fescue grass. Science 1986; 232(4749): 487–489. DOI: 10.1126/science.3008328.

Strickland

Looper

Matthews

, et al. Board-invited review: St. Anthony’s fire in livestock: causes, mechanisms, and potential solutions. J Anim Sci 2011; 89(5): 1603–1626. DOI: 10.2527/jas.2010-3478.

Dyer

. Evidence that ergovaline acts on serotonin receptors. Life Sci 1993; 53(14): PL223–PL228.

Klotz

Britt

Miller

Jr. , et al. Ergot alkaloid exposure during gestation alters: II. uterine and umbilical artery vasoactivity. J Anim Sci 2019; 97(4): 1891–1902. DOI: 10.1093/jas/skz069.

Weber

. Ergot compounds and brain function: neuroendocrine and neuropsychiatric aspects. New York, NY: Raven Press, 1980, pp. 25–34.

Klotz

. Activities and effects of ergot alkaloids on livestock physiology and production. Toxins 2015; 7(8): 2801–2821. DOI: 10.3390/toxins7082801.

Berde

. Ergot compounds: a synopsis. In: Goldstein

Lieberman

Calne

, et al. (eds) Ergot compounds and brain function: neuroendocrine and neuropsychiatric aspects. New York, NY: Raven Press, 1980, pp. 4–23.

Duckett

Andrae

Pratt

. Exposure to ergot alkaloids during gestation reduces fetal growth in sheep. Front Chemistry 2014; 2: 68. https://www.ncbi.nlm.nih.gov/pubmed/25191653. DOI: 10.3389/fchem.2014.00068.

10.

Greene

Britt

Powell

, et al. Ergot alkaloid exposure during gestation alters: 3. fetal growth, muscle fiber development, and miRNA transcriptome. J Anim Sci 2019; 97: 3153–3168. DOI: 10.1093/jas/skz153.

11.

Britt

Greene

Bridges

Jr ., et al. Ergot alkaloid exposure during gestation alters. I. maternal characteristics and placental development of pregnant ewes. J Animal Science 2019; 97(4): 1874–1890. DOI: 10.1093/jas/skz068. https://search.proquest.com/docview/2210302506

12.

Britt

Greene

Bridges

, et al. Ergot alkaloid exposure during gestation alters: I. maternal characteristics and placental development. J Anim Sci. 2019; 97: 1874–1890. DOI: 10.1093/jas/skz068.

13.

Britt

Powell

McMahan

, et al. The effect of ergot alkaloid exposure during gestation on the microscopic morphology and vasculature of the ovine placenta. J Histotechnology 2021; 44(4): 173–181. DOI: 10.1080/01478885.2021.1902670.

14.

Aiken

Flythe

. Vasoconstrictive responses by the carotid and auricular arteries in goats to ergot alkaloid exposure. Front Chem 2014 Nov 20; 2: 101. DOI: 10.3389/fchem.2014.00101.

15.

Ritchie

Oakes

Kennedy

, et al. Early gestational hypoxia and adverse developmental outcomes. Birth Defec Res 2017; 109(17): 1358–1376. DOI: 10.1002/bdr2.1136. https://onlinelibrary.wiley.com/doi/abs/10.1002/bdr2.1136

16.

Tong

Allison

Brain

, et al. Chronic hypoxia in ovine pregnancy recapitulates physiological and molecular markers of preeclampsia in the mother, placenta, and offspring. Hypertension (Dallas, Tex. 1979). Hypertension 2022; 79: 1525–1535. DOI: 10.1161/HYPERTENSIONAHA.122.19175. https://search.proquest.com/docview/2661953286

17.

Sales

Peralta

Narbona

, et al. Hypoxia and oxidative stress are associated with reduced fetal growth in twin and undernourished sheep pregnancies. Animals 2018; 8(11): 217. DOI: 10.3390/ani8110217.

18.

Barry

Anthony

. The pregnant sheep as a model for human pregnancy. Theriogenology 2008; 69(1): 55–67. DOI: 10.1016/j.theriogenology.2007.09.021

19.

Rottinghaus

Garner

Cornell

, et al. HPLC method for quantitating ergovaline in endophyte-infested tall fescue: seasonal variation of ergovaline levels in stems with leaf sheaths, leaf blades, and seed heads. J Agricul Food Chem 1991; 39(1): 112–115. DOI: 10.1021/jf00001a022

20.

Aiken

Strickland

Looper

, et al. Hemodynamics are altered in the caudal artery of beef heifers fed different ergot alkaloid concentrations. J Anim Sci 2009; 87(6): 2142–2150. DOI: 10.2527/jas.2008-1562.

21.

National Research Council . Nutrient requirements of small ruminants. Washington, DC: The National Academy Press, 2007.

22.

Vatnick

Ignotz

McBride

, et al. Effect of heat stress on ovine placental growth in early pregnancy. J Dev Physiol 1991; 16(3): 163–166.

23.

Stegeman

. A study of the maturation of the placenta in sheep. Acta Morphol Neerl Scand 1972; 10(4): 400.

24.

Bolger

Lohse

Usadel

. Trimmomatic: a flexible trimmer for illumina sequence data. bioinformatics. Bioinformatics 2014; 30(15): 2114–2120.

25.

TDNS

. Fast and SNP-tolerant detection of complex variants and splicing in short reads. Bioinformatics 2010; 26(7): 873–881. DOI: 10.1093/bioinformatics/btq057.

26.

Liao

Smyth

Shi

. Feature counts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 2014; 30(7): 923–930. DOI: 10.1093/bioinformatics/btt656.

27.

Robinson

McCarthy

Smyth

. edgeR: a bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 2010; 26(1): 139–140. DOI: 10.1093/bioinformatics/btp616.

28.

Wang

Han

, et al. cluster profiler: an R package for comparing biological themes among gene clusters. Omics (Larchmont, N.Y.) 2012; 16(5): 284–287. DOI: 10.1089/omi.2011.0118. https://www.liebertpub.com/doi/abs/10.1089/omi.2011.0118

29.

Britt

Noorai

Duckett

. Differentially expressed genes in cotyledon of ewes fed mycotoxins. BMC Genomics 2020; 21(1): 680 DOI: 10.1186/s12864-z.

30.

Livak

Schmittgen

. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-delta delta CT) method. Method 2001; 25(4): 402–408. DOI: 10.1006/meth.2001.1262.

31.

Britt

Greene

Wilbanks

, et al. Feeding tall fescue seed reduces ewe milk production, lamb birth weight and pre-weaning growth rate. Animals (Basel) 2020; 10(12): 2291. DOI: 10.3390/ani10122291. https://www.ncbi.nlm.nih.gov/pubmed/33287449

32.

Greene

Britt

Bertrand

, et al. Feeding tall fescue seed during mid and late gestation influences subsequent postnatal growth, puberty, and carcass quality of offspring. Animals (Basel) 2020; 10(10): 1859. DOI: 10.3390/ani10101859. https://search.proquest.com/docview/2451381062

33.

Aldrich

Rhodes

Miner

, et al. The effects of endophyte-infected tall fescue consumption and use of a dopamine antagonist on intake, digestibility, body temperature, and blood constituents in sheep. J Anim Sci 1993; 71: 158–163. DOI: 10.2527/1993.711158x.

34.

Burke

Jackson

Robson

. Seasonal changes in body weight and condition, and pregnancy and lambing rates of sheep on endophyte-infected tall fescue in the south-eastern United States. Sm Rum Res 2002; 44(2): 141–151. DOI: 10.1016/S0921-4488(02)00045-7.

35.

Parish

McCann

Watson

, et al. Use of nonergot alkaloid-producing endophytes for alleviating tall fescue toxicosis in sheep. J Anim Sci 2003; 81: 1316–1322. doi: 10.2527/2003.8151316x.4.

36.

Duckett

Andrae

Pratt

. Exposure to ergot alkaloids during gestation reduces fetal growth in sheep. Front Chem 2014; 2: 68. DOI: 10.3389/fchem.2014.00068.

37.

Ehrhardt

Bell

. Growth and metabolism of the ovine placenta during mid-gestation. Placenta 1995; 16(8): 727–741. DOI: 10.1016/0143-4004(95)90016-0.

38.

Redmer

Wallace

Reynolds

. Effect of nutrient intake during pregnancy on fetal and placental growth and vascular development. Domest Anim Endo 2004; 27: 199–217. DOI: 10.1016/j.domaniend.2004.06.006.

39.

Barcroft

Barron

. Observations upon the form and relations of the maternal and fetal vessels in the placenta of the sheep. Anat Rec 1946; 94: 569–595. DOI: 10.1002/ar.1090940403.

40.

Alexander

. Studies on the placenta of the sheep (ovis aries L.). J Reprod Fertil 1964; 7: 289–305.

41.

Hoet

Hanson

. Intrauterine nutrition: its importance during critical periods for cardiovascular and endocrine development. J Physiol 1999; 514: 617–627. DOI: 10.1111/j.1469-7793.1999.617ad.x.

42.

Osgerby

Wathes

Howard

, et al. The effect of maternal undernutrition on the placental growth trajectory and the uterine insulin-like growth factor axis in the pregnant ewe. J Endocrinol 2004; 182(1): 89–103. DOI: 10.1677/joe.0.1820089.

43.

Penninga

Longo

. Ovine placentome morphology: effect of high altitude, long-term hypoxia. Placenta 1998; 19(2–3): 187–193. DOI: 10.1016/s0143-4004(98)90008-x.

44.

Vonnahme

Hess

Nijland

, et al. Placentomal differentiation may compensate for maternal nutrient restriction in ewes adapted to harsh range conditions. J Anim Sci 2006; 84(12): 3451–3459. DOI: 10.2527/jas.2006-132.

45.

Vonnahme

Arndt

Johnson

, et al. Effect of morphology on placentome size, vascularity, and vasoreactivity in late pregnant sheep. Biol Reprod 2008; 79(5): 976–982. DOI: 10.1095/biolreprod.108.070748.

46.

Fowden

Sferruzzi-Perri

Coan

, et al. Placental efficiency and adaptation: Endocrine regulation. J Physiology 2009; 587(14): 3459–3472. DOI: 10.1113/jphysiol.2009.173013.

47.

Rattray

Garrett

East

, et al. Growth, development and composition of the ovine conceptus and mammary gland during pregnancy. J Anim Sci 1974; 38: 613–626. DOI: 10.2527/jas1974.383613x.

48.

Greenwood

Bell

. Developmental programming and growth of livestock tissues for meat production. Vet Clin North Am Food Anim Pr 2019; 35: 303–319. DOI: 10.1016/j.cvfa.2019.02.008.

49.

Louey

Cock

Harding

. Long term consequences of low birthweight on postnatal growth, adiposity and brain weight at maturity in sheep. J Reprod Dev 2005; 51: 59–68. DOI: 10.1262/jrd.51.59.

50.

Symonds

Sebert

Budge

. Nutritional regulation of fetal growth and implications for productive life in ruminants. Animal 2010; 4: 1075–1083. DOI: 10.1017/S1751731110000479.

51.

Jerber

Baas

Soulavie

, et al. The coiled-coil domain containing protein CCDC151 is required for the function of IFT-dependent motile cilia in animals. Hum Mol Genet 2014; 23(3): 563–577. DOI: 10.1093/hmg/ddt445.

52.

Holobotovskyy

Chong

Leader

, et al. RGS5 integrates angiotensin II and PPAR vascular signaling to regulate blood pressure during pregnancy. Microcirc 2015; 22(7): 36. DOI: 10.1111/micc.12246.

53.

Goyal

Yellon

Longo

, et al. Placental gene expression in a rat ‘model’ of placental insufficiency. Placenta 2010; 31(7): 568–575.

54.

Padua

Hansen

. Evolution and function of the uterine serpins (SERPINA14). Am J Reprod Immunol 2010; 64(4): 265–274.

55.

Alpy

Tomasetto

. Give lipids a START: the StAR-related lipid transfer (START) domain in mammals. J Cel Sci 2005; 118(13): 2791–2801. DOI: 10.1242/jcs.02485.

56.

Rodriguez-Agudo

Malacrida

Kakiyama

, et al. StarD5: an ER stress protein regulates plasma membrane and intracellular cholesterol homeostasis. J Lipid Research 2019; 60(6): 1087–1098. DOI: 10.1194/jlr.M091967.

57.

Stuedemann

Rumsey

Bond

, et al. Association of blood cholesterol with occurrence of fat necrosis in cows and tall fescue summer toxicosis in steers. Am J Veter Res 1985; 46(9): 1990–1995. https://agris.fao.org/agris-search/search.do?recordID=US8633951

58.

Edwards

Dunlap

Spencer

, et al. Identification of pathways associated with placental adaptation to maternal nutrient restriction in sheep. Genes 2020; 11: 1031. DOI: 10.3390/genes11091031.

59.

Rocha

da Silva Andrade

de Melo

, et al. Early pregnancy-induced transcripts in peripheral blood immune cells in bos indicus heifers. Sci Rep 2020; 10(1): 13733. DOI: 10.1038/s41598-020-70616-8. https://www.ncbi.nlm.nih.gov/pubmed/32792605

60.

Kay

Madan

. Fertility defects in surfactant associated protein D knockout female mice: altered ovarian hormone profile. Mol Immunol 2016; 71: 87–97. DOI: 10.1016/j.molimm.2016.01.002.

61.

Jia

Huang

, et al. Dysregulated DNA methyltransferase 3A upregulates IGFBP5 to suppress trophoblast cell migration and invasion in preeclampsia. Hypertension 2017; 69: 356–366. DOI: 10.1161/hypertensionaha.116.08483.

62.

Perschbacher

Deng

Fisher

, et al. Regulators of G protein signaling in cardiovascular function during pregnancy. Physiol Genomics 2018; 50(8): 590–604. . DOI: 10.1152/physiolgenomics.00037.2018. https://www.ncbi.nlm.nih.gov/pubmed/29702036

63.

Holobotovskyy

Chong

Burchell

, et al. Regulator of G protein signaling 5 is a determinant of gestational hypertension and preeclampsia. Sci Transla Med 2015; 7(290): 290ra88. https://www.ncbi.nlm.nih.gov/pubmed/26041705. DOI: 10.1126/scitranslmed.aaa5038.

64.

Burton

Lowden

. The placenta: a multifaceted, transient organ Philos Trans R Soc Lond B Biol Sci 2015; 370(1663): 20140066. https://dx.doi.org/10.1098%2Frstb.2014.0066

65.

Hayashi

Kuroda

Kishimoto

, et al. Downregulation of rRNA transcription triggers cell differentiation. PLoS ONE 2014; 9(5): e98586. DOI: 10.1371/journal.pone.0098586.