Infertility is a longstanding limitation in livestock production with important economic impact for the cattle industry. Female reproductive traits are polygenic and lowly heritable in nature, thus selection for fertility is challenging. Beef cattle operations leverage estrous synchronization in combination with artificial insemination (AI) to breed heifers and benefit from an early and uniform calving season. A couple of weeks following AI, heifers are exposed to bulls for an opportunity to become pregnant by natural breeding (NB), but they may also not become pregnant during this time period. Focusing on beef heifers, in their first breeding season, we hypothesized that: a- at the time of AI, the transcriptome of peripheral white blood cells (PWBC) differs between heifers that become pregnant to AI and heifers that become pregnant late in the breeding season by NB or do not become pregnant during the breeding season; and b- the ratio of transcript abundance between genes in PWBC classifies heifers according to pregnancy by AI, NB, or failure to become pregnant. We generated RNA-sequencing data from 23 heifers from two locations (A: six AI-pregnant and five NB-pregnant; and B: six AI-pregnant and six non-pregnant). After filtering out lowly expressed genes, we quantified transcript abundance for 12,538 genes. The comparison of gene expression levels between AI-pregnant and NB-pregnant heifers yielded 18 differentially expressed genes (DEGs) (ADAM20, ALDH5A1, ANG, BOLA-DQB, DMBT1, FCER1A, GSTM3, KIR3DL1, LOC107131247, LOC618633, LYZ, MNS1, P2RY12, PPP1R1B, SIGLEC14, TPPP, TTLL1, UGT8, eFDR≤0.02). The comparison of gene expression levels between AI-pregnant and non-pregnant heifers yielded six DEGs (ALAS2, CNKSR3, LOC522763, SAXO2, TAC3, TFF2, eFDR≤0.05). We calculated the ratio of expression levels between all gene pairs and assessed their potential to classify samples according to experimental groups. Considering all samples, relative expression from two gene pairs correctly classified 10 out of 12 AI-pregnant heifers (P = 0.0028) separately from the other 11 heifers (NB-pregnant, or non-pregnant). The transcriptome profile in PWBC, at the time of AI, is associated with the fertility potential of beef heifers. Transcript levels of specific genes may be further explored as potential classifiers, and thus selection tools, of heifer fertility.

Artificial insemination is a preferred breeding method for beef heifers as it advances the genetic background, produces a predictive and profitable calving season, and extends the heifer’s reproductive life span. As reproductive efficiency in heifers is key for the success of beef cattle production systems, following artificial insemination, heifers are exposed to a bull for the remainder of the breeding season. Altogether, up to 95% of heifers might become pregnant in their first breeding season. Heifers that do not become pregnant at the end of the breeding season represent an irreparable economical loss. Additionally, heifers conceiving late in the breeding season to natural service, although acceptable, poses serious losses to producers. To minimize losses due to reproductive failure, different phenotypic parameters can be assessed and utilized as selection tools. Here, we tested the hypothesis that in a group of pre-selected heifers, records of weaning weight, age at weaning, age at artificial insemination, and age of dam differ among heifers of varied reproductive outcomes during the first breeding season. None of the parameters tested presented predictive ability to discriminate the heifers based on the response variable (‘pregnant to artificial insemination’, ‘pregnant to natural service’, ‘not pregnant’). Heifers categorized with body condition score = 6 and reproductive tract score ≥ 4 had the greatest proportion of pregnancy to artificial insemination (49% and 44%, respectively). Furthermore, it was notable that heifers presenting body condition score = 6 and reproductive tract score = 5 presented the greatest pregnancy rate at end of the breeding season (89%). Heifers younger than 368 d at the start of the breeding season did not become pregnant to artificial insemination. Those young heifers had 12.5% chance to become pregnant in their first breeding season, compared to 87.5% if the heifers were older than 368 days. Our results suggest that beef heifers with body condition score = 6 and reproductive tract score ≥ 4 are more likely to become pregnant to artificial insemination. Careful assessment should be undertaken when developing replacement heifers that will not reach 12 months of age by the beginning of the breeding season.

Induced ovulation of small pre-ovulatory follicles reduced pregnancy rates, embryo survival, day seven embryo quality, and successful embryo cleavage in beef cows undergoing fixed-time artificial insemination. RNA-sequencing of oocytes and associated cumulus cells collected from pre-ovulatory follicles 23 h after gonadotropin-releasing hormone (GnRH) administration to induce the pre-ovulatory gonadotropin surge suggested reduced capacity for glucose metabolism in cumulus cells of follicles ≤11.7 mm. We hypothesized that the follicular fluid metabolome influences metabolic capacity of the cumulus-oocyte complex and contributes to reduced embryo cleavage and quality grade observed following induced ovulation of small follicles. Therefore, we performed a study to determine the correlation between pre-ovulatory follicle diameter and follicular fluid metabolome profiles in lactating beef cows (Angus, n = 130). We synchronized the development of a pre-ovulatory follicle and collected the follicular contents approximately 20 h after GnRH administration. We then performed ultra-high performance liquid chromatography—high resolution mass spectrometry (UHPLC-HRMS) metabolomic studies on 43 follicular fluid samples and identified 38 metabolites within pre-ovulatory follicles of increasing size. We detected 18 metabolites with a significant, positive correlation to follicle diameter. Individual and pathway enrichment analysis of significantly correlated metabolites suggest that altered glucose and amino acid metabolism likely contribute to reduced developmental competence of oocytes when small pre-ovulatory follicles undergo induced ovulation.

The preovulatory intrafollicular environment plays a major role in determining oocyte competence. The basis of this review is to highlight the importance of the preovulatory follicle’s physiological status prior to the preovulatory luteinizing hormone (LH) surge and onset of oocyte maturation to promote an optimal follicular microenvironment and optimal oocyte developmental competence in cattle. While the underlying mechanisms remain unclear, and are likely multifactorial, the preovulatory follicle’s physiological status prior to the preovulatory LH surge is highly influential on the oocyte’s capacity to undergo postfertilization embryo development. Changes in the intrafollicular environment of the preovulatory follicle including steroid hormone production, metabolome profiles, and proteome profiles likely support the oocyte’s developmental and metabolic competency. This review focuses on the relationship between bovine oocyte developmental competency and antral follicle progression to the preovulatory phase, the role of the preovulatory follicle in improving oocyte developmental competence in cattle, and the importance of the ever-evolving preovulatory intrafollicular environment for optimal fertility. Bovine pregnancy rates and oocyte developmental competence are heavily influenced by the periovulatory follicular environment. It is well known that the status of the preovulatory follicle at the time of the luteinizing hormone (LH) surge is related to both circulating and intrafollicular hormone concentrations during the follicular phase. Additional relationships between follicle status at the time of the LH surge and oocyte metabolic capacity or modifications in the follicular fluid metabolome and proteome have recently been established. Such studies suggest that critical, multifaceted modifications to the intrafollicular components occur leading up to the LH surge, and that such modifications contribute to the optimal preparation of both the oocyte and intrafollicular environment for oocyte maturation. This review focuses on intrafollicular changes that occur within the dominant follicle from luteolysis to the LH surge and discusses recent advancements in the literature related to how such changes support oocyte competence.

Extremes in body condition reduce fertility and overall productivity in beef cattle herds, due in part to altered systemic metabolic conditions that influence the intrafollicular and uterine environment. Follicular fluid and serum metabolome profiles are influenced by body composition in women and dairy cattle; however, such information is lacking in beef cattle. We hypothesized that body condition score (BCS)-related alterations in the metabolome of preovulatory follicular fluid and serum may influence oocyte maturation while impacting the oviductal or uterine environment. Therefore, we performed a study with the objective to determine the relationship between BCS and the metabolome of follicular fluid and serum in lactating beef cattle. We synchronized the development of a preovulatory follicle in 130 cows of varying BCS. We collected blood and performed transvaginal follicle aspirations to collect follicular fluid from the preovulatory follicle ~18 h after gonadotropin-releasing hormone administration to stimulate the preovulatory gonadotropin surge. We then selected follicular fluid and serum samples from cows with BCS 4 (Thin; n = 14), BCS 6 (Moderate; n = 18), or BCS >8 (Obese; n = 14) for ultra-high performance liquid chromatography-high resolution mass spectrometry. We identified differences in the follicular fluid or serum of thin, moderate, and obese animals based on multiple linear regression. MetaboAnalyst 5.0 was used for enrichment analysis of significant metabolites. We identified 38 metabolites in follicular fluid and 49 metabolites in serum. There were no significant differences in follicular fluid metabolite content among BCS classifications. There were 5, 22, and 1 serum metabolites differentially abundant between thin-obese, moderate-thin, and moderate-obese classifications, respectively (false discovery rate [FDR] < 0.10). These metabolites were enriched in multiple processes including “arginine biosynthesis,” “arginine/proline metabolism,” and “D-glutamine/D-glutamate metabolism” (FDR < 0.04). Pathways enriched with serum metabolites associated with BCS indicate potentially increased reactive oxygen species (ROS) in serum of thin cows. ROS crossing the blood follicular barrier may negatively impact the oocyte during oocyte maturation and contribute to the reduced pregnancy rates observed in thin beef cows. Extremes in body condition affect fertility and pregnancy outcomes in beef cows. Much research has been done in women and dairy cows to evaluate body condition’s effect on oocyte and embryo quality, pregnancy rates, and pregnancy outcomes. However, little work of this type has been done in beef cows and most studies do not focus on the preovulatory time period. The preovulatory time period is an essential time for the oocyte, as final stages of prematuration and the completion of oocyte maturation take place in the peri-ovulatory follicle. The follicular fluid provides the microenvironment for oocyte maturation and exchanges substances with maternal circulation at the blood follicular barrier. Alterations in maternal circulation due to extremes in body condition may pass into the follicular fluid and affect the oocyte during the preovulatory time period. Such conditions may contribute to the reduced fertility seen in beef cows with extreme body condition.

The rumen is a complex organ that is critical for its host to convert low-quality feedstuffs into energy. The conversion of lignocellulosic biomass to volatile fatty acids and other end products is primarily driven by the rumen microbiome and its interaction with the host. Importantly, the rumen is demarcated into five distinct rumen sacs as a result of anatomical structure, resulting in variable physiology among the sacs. However, rumen nutritional and microbiome studies have historically focused on the bulk content or fluids sampled from single regions within the rumen. Examining the rumen microbiome from only one or two biogeographical regions is likely not sufficient to provide a comprehensive analysis of the rumen microbiome and its fermentative capacity. Rumen biogeography, digesta fraction, and microbial rumen–tissue association all impact the diversity and function of the entirety of the rumen microbiome. Therefore, this review discusses the importance of the rumen biographical regions and their contribution to microbiome variation.