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Despite collective efforts to understand the complex regulation of reproductive traits, no causative genes and/or mutations have been reported yet. By integrating genomics and transcriptomics data, potential regulatory mechanisms may be unveiled, providing opportunities to dissect the genetic factors governing fertility. Herein, we identified regulatory variants from RNA-Seq data associated with gene expression regulation in the uterine luminal epithelial cells of beef cows. We identified 4676 cis and 7682 trans eQTLs (expression quantitative trait loci) affecting the expression of 1120 and 2503 genes, respectively (FDR < 0.05). These variants affected the expression of transcription factor coding genes (71 cis and 193 trans eQTLs) and genes previously reported as differentially expressed between pregnant and nonpregnant cows. Functional over-representation analysis highlighted pathways related to metabolism, immune response, and hormone signaling (estrogen and GnRH) affected by eQTL-regulated genes (p-value ≤ 0.01). Furthermore, eQTLs were enriched in QTL regions for 13 reproduction-related traits from the CattleQTLdb (FDR ≤ 0.05). Our study provides novel insights into the genetic basis of reproductive processes in cattle. The underlying causal mechanisms modulating the expression of uterine genes warrant further investigation. [ABSTRACT FROM AUTHOR]

Reproduction plays a major role in the production efficiency of livestock species. However, cow-centric reproductive traits tend to be lowly heritable and are not expressed until later in an animal's lifetime, making phenotypic selection alone inefficient at generating genetic gain. Genetic progress can be accelerated by focusing selection on the predicted genetic component of reproductive traits using Expected Progeny Differences. We used the American Simmental Association's performance and Total Herd Enrollment data, made up of 533,155 calving records from 303,158 females (132,403 cows and 170,755 heifers), 33,732 of which are genotyped, to explore three continuous and two discrete phenotypes focused on quantifying early and sustained fertility in beef cows. We analyzed calving date (CD) (cow's CD relative to the start of the calving season), calving interval (CI) (days between calves), first calving interval (FCI) (CI observation between the first and second calving record for a female), heifer pregnancy (HP) (did the animal calve as 2-yr-old), and discrete early calving (DEC) (did animal calve in the first 30 d of the calving season) as distinct, but correlated measures of fertility. This dataset provides insight into population-wide trends related to cow attrition, calving season lengths, and phenotypic variation in fertility. We used pedigree and genomic REML to estimate these six phenotypes' genetic, permanent environment, and temporary environmental variance components. Pedigree-estimated heritabilities were 0.06 (± 0.000011) for CD, (0.04 ± 0.000005) for CI, 0.07 (± 0.000016) for DEC, 0.05 ± 0.000041 for FCI, and 0.23 (± 0.000099) for HP, consistent with other fertility traits across beef and dairy cattle. The incorporation of genomics increased the heritability estimate for HP (0.24 ± 0.000098) and decreased the estimate for FCI (0.04 ± 0.000029). Positive phenotypic and genetic correlations were found among these phenotypes (rG   = 0.01 to 0.96). These results call for further work in optimizing genetic predictions and exploration of the genetic architecture through genome-wide studies. Whole herd reporting date frameworks represent opportunities for measuring new reproductive phenotypes, but their utility in genetic evaluations will rely on novel trait initiatives and consistent recording that captures more detailed data. [ABSTRACT FROM AUTHOR]

Simple Summary: In South African beef cattle smallholder farms, there has been no recommended target benchmark that provide a baseline for improving the reported low herd reproductive performances. A multi-stage sampling approach was performed to examine reproductive performance as defined by pregnancy rate, fetal and calf losses, calving interval and days open to benchmark smallholder herd reproduction. It was found that smallholder farms recorded on average, 50% pregnancy rate and 12% fetal and calf losses, with days open and calving interval achieved at 334 and 608 days, respectively. Targeted benchmarks for performance derived from this study were 54%, 1.4%, 152 and 425 days, respectively for pregnancy rate, fetal and calf losses, days open and calving interval for smallholder farms in South Africa. The study showed that herd management practices including non-culling of old and non-productive cows, no knowledge of body condition score prior to breeding, no record keeping, continuous breeding season and low bull to cow ratio are associated with recorded reproductive performance norms in smallholder farms. The study found that smallholders have the potential to improve their performance levels if management knowledge is provided through advisory and extension services. Smallholder beef cattle farms in South Africa have had low reproductive performance, which has been associated with management practices. Considering current farm management practices, a multi-stage selection study was conducted to assess reproductive performance as defined by pregnancy rate, fetal and calf losses, calving interval and days open to benchmark reproductive performance. Data were collected twice, in autumn (March–May) for pregnancy diagnosis and in spring (September–November) for monitoring of confirmed pregnancies. Overall, 3694 cow records from 40 smallholder herds were collected during 2018 and 2019 breeding seasons from five provinces. The preferred 25th quartile described target performance and GLIMMIX procedure determined associations between management practices and performance. Smallholder farms on average recorded 50% pregnancy rate and 12% fetal and calf losses with 304 and 608 days open and calving interval, respectively. The derived target benchmarks for pregnancy rate, fetal and calf losses, days open and calving intervals in smallholder farms were 54%, 1.4%, 152 and 425 days, respectively. Reproductive performance was associated with no knowledge of body condition scoring before breeding, culling of old and non-productive cows, record keeping and low bull to cow ratio (p < 0.05). The performance benchmarks implied that industry averages may be improved if sustainable management services are provided through extension and advisory services. [ABSTRACT FROM AUTHOR]

Simple Summary: Female reproductive failure is still a challenge for the beef industry. Several biological processes that underlie fertility-related traits, such as the establishment of pregnancy and embryo survival, are still unclear. Increased availability of transcriptomic data has allowed a deep investigation of the potential mechanisms involved in fertility. This study investigated candidate gene biomarkers predictive of pregnancy status and underlying fertility-related networks. To this end, we integrated gene expression profiles through supervised machine learning and gene network modeling. We identified nine biologically relevant endometrial gene biomarkers that could discriminate against pregnancy status in cows. These biomarkers were co-expressed with genes critical for uterine receptivity, including endometrial tissue remodeling, focal adhesion, and embryo development. This study outlined key pathways involved with pregnancy success and provided predictive candidate biomarkers for pregnancy outcome in cows. Reproductive failure is still a challenge for beef producers and a significant cause of economic loss. The increased availability of transcriptomic data has shed light on the mechanisms modulating pregnancy success. Furthermore, new analytical tools, such as machine learning (ML), provide opportunities for data mining and uncovering new biological events that explain or predict reproductive outcomes. Herein, we identified potential biomarkers underlying pregnancy status and fertility-related networks by integrating gene expression profiles through ML and gene network modeling. We used public transcriptomic data from uterine luminal epithelial cells of cows retrospectively classified as pregnant (P, n = 25) and non-pregnant (NP, n = 18). First, we used a feature selection function from BioDiscML and identified SERPINE3, PDCD1, FNDC1, MRTFA, ARHGEF7, MEF2B, NAA16, ENSBTAG00000019474, and ENSBTAG00000054585 as candidate biomarker predictors of pregnancy status. Then, based on co-expression networks, we identified seven genes significantly rewired (gaining or losing connections) between the P and NP networks. These biomarkers were co-expressed with genes critical for uterine receptivity, including endometrial tissue remodeling, focal adhesion, and embryo development. We provided insights into the regulatory networks of fertility-related processes and demonstrated the potential of combining different analytical tools to prioritize candidate genes. [ABSTRACT FROM AUTHOR]

The aim of the study was to analyse the relationship between the somatic cell counts in the milk (the udder health status indicator) and the cow's fertility, taking the influence of the selected factors into account. The udder health status was determined based on the somatic cell count of the milk from 88 745 test-day records from 55 685 Polish Holstein-Friesian cows. The test-day measurements were made up to 30 days before the first insemination, during the period up to 180 days of the first and second lactation. Because the somatic cell count showed high variation and is not normally distributed, the data were transformed to the natural logarithm scale. Based on the results of the statistical analysis, it was shown that with the increase in the number of somatic cells in the milk, the calving intervals were extended by 11 days (P ≤ 0.01), the service period by around 4 days (P ≤ 0.05), the increase in the services per conception by 0.11 (P ≤ 0.01). There was a statistically significant correlation, weak on the Guilford scale, between the natural logarithm of the somatic cell count and the fertility of the cows: the calving interval - CI (r = 0.050**, P ≤ 0.01), service period - SP (r = 0.016**) end services per conception - SPC (r = 0.019**). Monitoring the number of somatic cells in the milk could contribute to improving the fertility of the cows in particular: in the second lactation in the double lactation (for the CI (r = 0.059**)); in herds with a production level of 7000-9000 kg of milk (for the CI (r = 0.055**), the SP (r = 0.022**) and the SPC (r = 0.024**)); the daily productivity of > 40 kg (for the CI (r = 0.052**), the SP (r = 0.033**) and the SPC (r = 0.029**)), the number of cows in the herd of > 200 (for the CI (r = 0.061**), the SP (r = 0.034**) and the SPC (r = 0.033**)), in the autumn season of the first insemination (for the CI (r = 0.072**), the SP (r = 0.027**) and the SPC (r = 0.031**)). The magnitude of these correlations varied within the classes of the factors such as the daily production level, the age of cows´ lactation number, the season of the first insemination, the herd production level, and the herd size. It appears that the somatic cell count results obtained from the periodic milk recording, considered as an indirect measure of the udder health and used when deciding on the mastitis treatment, could be a useful tool for controlling the fertility in the cows.

Reproductive efficiency is major determinant of the dairy herd profitability. Thus, reproductive traits have been widely used as selection objectives in the current dairy cattle breeding programs. We aimed to evaluate strategies to model days open (DO), calving interval (CI) and daughter pregnancy rate (DPR) in Brazilian Holstein cattle. These reproductive traits were analysed by the autoregressive (AR) model and compared with classical repeatability (REP) model using 127,280, 173,092 and 127,280 phenotypic records, respectively. The first three calving orders of cows from 1,469 Holstein herds were used here. The AR model reported lower values for Akaike Information Criteria and Mean Square Errors, as well as larger model probabilities, for all evaluated traits. Similarly, larger additive genetic and lower residual variances were estimated from AR model. Heritability and repeatability estimates were similar for both models. Heritabilities for DO, CI and DPR were 0.04, 0.07 and 0.04; and 0.05, 0.06 and 0.04 for AR and REP models, respectively. Individual EBV reliabilities estimated from AR for DO, CI and DPR were, in average, 0.29, 0.30 and 0.29 units higher than those obtained from REP model. Rank correlation between EBVs obtained from AR and REP models considering the top 10 bulls ranged from 0.72 to 0.76; and increased from 0.98 to 0.99 for the top 100 bulls. The percentage of coincidence between selected bulls from both methods increased over the number of bulls included in the top groups. Overall, the results of model‐fitting criteria, genetic parameters estimates and EBV predictions were favourable to the AR model, indicating that it may be applied for genetic evaluation of longitudinal reproductive traits in Brazilian Holstein cattle. [ABSTRACT FROM AUTHOR]

Cow stayability plays a major role on the overall profitability of the beef cattle industry, as it is directly related to reproductive efficiency and cow's longevity. Stayability (STAY63) is usually defined as the ability of the cow to calve at least three times until 76 months of age. This is a late‐measured and lowly heritable trait, which consequently constrains genetic progress per time unit. Thus, the use of genomic information associated with novel stayability traits measured earlier in life will likely result in higher prediction accuracy and faster genetic progress for cow longevity. In this study, we aimed to compare pedigree‐based and single‐step GBLUP (ssGBLUP) methods as well as to estimate genetic correlations between the proposed stayability traits: STAY42, STAY53 and STAY64, which are measured at 52, 64 and 76 months of cow's age, considering at least 2, 3 and 4 calving, respectively. ssGBLUP yielded the highest prediction accuracy for all traits. The heritability estimates for STAY42, STAY53, STAY63 and STAY64 were 0.090, 0.151, 0.152 and 0.143, respectively. The genetic correlations between traits ranged from 0.899 (STAY42 and STAY53) to 0.985 (STAY53 and STAY63). The high genetic correlation between STAY42 and STAY53 suggests that besides being related to cow longevity, STAY53 is also associated with the early‐stage reproductive efficiency. Thus, STAY53 is recommended as a suitable selection criterion for reproductive efficiency due to its higher heritability, favourable genetic correlation with other traits, and measured earlier in life, compared with the conventional stayability trait, that is STAY63. [ABSTRACT FROM AUTHOR]

Abstract Background Drivers of change in dairy herd health management include the significant increase in herd/farm size, quota removal (within Europe) and the increase in technologies to aid in dairy cow reproductive management. Main body There are a number of key areas for improving fertility management these include: i) handling of substantial volumes of data, ii) genetic selection (including improved phenotypes for use in breeding programmes), iii) nutritional management (including transition cow management), iv) control of infectious disease, v) reproductive management (and automated systems to improve reproductive management), vi) ovulation / oestrous synchronisation, vii) rapid diagnostics of reproductive status, and viii) management of male fertility. This review covers the current status and future outlook of many of these key factors that contribute to dairy cow herd health and reproductive performance. Conclusions In addition to improvements in genetic trends for fertility, numerous other future developments are likely in the near future. These include: i) development of new and novel fertility phenotypes that may be measurable in milk; ii) specific fertility genomic markers; iii) earlier and rapid pregnancy detection; iv) increased use of activity monitors; v) improved breeding protocols; vi) automated inline sensors for relevant phenotypes that become more affordable for farmers; and vii) capturing and mining multiple sources of “Big Data” available to dairy farmers. These should facilitate improved performance, health and fertility of dairy cows in the future.

The aim of the study was to analyse the relationship between the somatic cell counts in the milk (the udder health status indicator) and the cow's fertility, taking the influence of the selected factors into account. The udder health status was determined based on the somatic cell count of the milk from 88 745 test-day records from 55 685 Polish Holstein-Friesian cows. The test-day measurements were made up to 30 days before the first insemination, during the period up to 180 days of the first and second lactation. Because the somatic cell count showed high variation and is not normally distributed, the data were transformed to the natural logarithm scale. Based on the results of the statistical analysis, it was shown that with the increase in the number of somatic cells in the milk, the calving intervals were extended by 11 days (P = 0.01), the service period by around 4 days (P = 0.05), the increase in the services per conception by 0.11 (P = 0.01). There was a statistically significant correlation, weak on the Guilford scale, between the natural logarithm of the somatic cell count and the fertility of the cows: the calving interval - CI (r = 0.050**, P = 0.01), service period - SP (r = 0.016**) end services per conception - SPC (r = 0.019**). Monitoring the number of somatic cells in the milk could contribute to improving the fertility of the cows in particular: in the second lactation in the double lactation (for the CI (r = 0.059**)); in herds with a production level of 7000-9000 kg of milk (for the CI (r = 0.055**), the SP (r = 0.022**) and the SPC (r = 0.024**)); the daily productivity of > 40 kg (for the CI (r = 0.052**), the SP (r = 0.033**) and the SPC (r = 0.029**)), the number of cows in the herd of > 200 (for the CI (r = 0.061**), the SP (r = 0.034**) and the SPC (r = 0.033**)), in the autumn season of the first insemination (for the CI (r = 0.072**), the SP (r = 0.027**) and the SPC (r = 0.031**)). The magnitude of these correlations varied within the classes of the factors such as the daily production level, the age of cows' lactation number, the season of the first insemination, the herd production level, and the herd size. It appears that the somatic cell count results obtained from the periodic milk recording, considered as an indirect measure of the udder health and used when deciding on the mastitis treatment, could be a useful tool for controlling the fertility in the cows. [ABSTRACT FROM AUTHOR]

Characterization of reproductive traits in Mirandesa beef cattle is important for breed improvement and conservation, mainly due to its little genetic diversity. Reduced individual and maternal performance is often associated with inbreeding depression, which could be further aggravate the environmental effects. In this study, 7386 herd records for Mirandesa were used to characterize the main reproductive traits, like age at first calving (AFC), pregnancy length (PL), calving interval (CI), yearly calving distribution (CD) and productive lifespan (PLf). The non-genetic effects were tested using non-parametric methods, as the target variables were not normally distributed. The median for AFC in Mirandesa was close to 32 months; AFC was affected by the production system, farm and by the year and season of birth. The mean for PL was 287±8.9 days, being affected by parity and calf gender. The median CI, of 378 days, was only affected by the breeding program, parity, season and year. Calving season was unevenly distributed over the year, showing different patterns after the production system. The mean productive lifespan of Mirandesa was 6.45 years, though 20% of the cows presented a PLf longer than ten years. The main non-genetic effects suggested that farmer's decision and nutrition may constrain the expression of the reproductive traits in Mirandesa breed. This aspect needs to be addressed when designing any breeding programs which should prioritise for the increase in the number of calves per year along with a careful selection of reproducers to decrease reported inbreeding. [ABSTRACT FROM AUTHOR]

Female fertility significantly affects the efficiency of cow-calf production. Despite the collective efforts to understand the complex regulation of reproductive traits, causative genes and/or mutations have yet to be reported. Using omics technologies, such as gene expression, may unveil potential regulatory mechanisms and provide opportunities that link genotype to phenotype. Among them, expression quantitative trait loci (eQTL) are a powerful tool to identify biological mechanisms and potential markers for improving fertility. This study aimed to identify eQTLs underlying fertility-related traits and their co-localization with previously annotated QTLs. RNA-Seq from uterine epithelial cells (GSE171577) from crossbreed cows (n = 18 non-pregnant - NP and n = 25 pregnant - P) were used for gene expression analysis and SNP calling. Raw data quality control was performed, and read mapping was carried out using STAR. Genes were normalized to counts per million (CPM) and then the CPM values were log2 transformed using edgeR. Next, uniquely mapped reads were used for variant detection using the GATK software. Significant eQTLs were compared with the Animal Genome cattle database (QTLdb) to identify overlapping QTL regions. After quality control, 43 samples, 203,404 SNPs, and 15,029 genes were used for eQTL analysis. Using an additive linear model from the Matrix eQTL R-package, we identified 3,989 cis- and 7,683 trans-eQTLs for 1,120 and 2,503 genes, respectively (FDR < 0.05). A total of 50 cis-eQTLs were previously reported as differentially expressed genes, including CD37, CXCL3, PILRA, and PPP6R1 genes. The QTLs from QTLdb overlapping with our eQTLs were associated with traits such as age at puberty, conception rate, fertility index, and luteal activity (FDR < 0.05). Additionally, QTLs for production traits, such as milk production and body weight gain, were over-represented by the eQTLs we have identified. Significant biological processes underlying cis-regulated genes retrieved from ShinyGO were related to antigen processing and presentation. Likewise, trans-eQTLs genes were involved with transcription cisregulatory region binding and transcription regulator activity. Our study provides novel regulatory and potential causative genetic variants, biological pathways, and genes underlying fertility in cows. Annotation and co-localization of detected eQTLs retrieved genomic regions previously reported as QTLs for production and reproduction-related traits. Further investigation, however, is required to untangle the mechanisms modulating gene expression and its effects on fertilityrelated traits. [ABSTRACT FROM AUTHOR]

After parturition, cows undergo negative energy balance leading to fat mobilization, predisposing them to fatty liver syndrome and ketosis with major consequences for health and reproduction. Supplementation of rumen-protected choline (RPC) has attracted major research efforts during the last decade, assuming that choline improves liver function by increasing very low-density lipoprotein exportation from the liver, thereby improving metabolic profiles, milk production, and reproduction. However, the effects of RPC on production, health, and reproduction have been inconsistent. Therefore, the aim of this meta-analysis was to evaluate the effects of RPC supplementation, starting from d 20 (± 12.2) ante partum to d 53 (± 31.0) postpartum, on feed intake, milk production performance and metabolic profiles of dairy cows early postpartum. Data analyses from 27 published studies showed an increase in postpartal dry matter intake (from on average 19.1 to 19.9 kg/d; p < 0.01) and milk yield (from on average 31.8 to 32.9 kg/d; p = 0.03) in cows receiving RPC. Milk fat yield and milk protein yield were also increased (p ≤ 0.05), without changing milk protein and fat contents. However, no interactive effects between cow’s milk yield level and RPC-supplementation as well as no dose-dependent effects of RPC supplementation were observed. Supplementing the diet with RPC showed no effects on blood metabolites (non-esterified fatty acids, beta-hydroxybutyrate, glucose, and cholesterol), independent of the milk yield level of the cows. An effect on liver triacylglycerol contents, incidence of ketosis, and mastitis could not be confirmed across all studies included in this meta-analysis. Also, the positive effects of RPC supplementation on reproductive performance were not consistent findings. In conclusion, supplementing RPC in lactating dairy cows showed positive effects on dry matter intake which likely caused the improved milk yield. However, RPC supplementation did not improve the metabolic health status of the cows. As several factors might be related to the responses to RPC, further research is needed to explore the precise mechanisms of RPC action in lactating cows, especially with regards to feed intake improvement and its related metabolic health-promoting potential in early lactating dairy cows.

Progesterone (P4) from the corpus luteum is critical for the establishment and maintenance of pregnancy and plays a major role in regulating endometrial secretions essential for stimulating and mediating changes in conceptus growth and differentiation throughout early pregnancy in ruminants. Numerous studies have demonstrated an association between elevated systemic P4 and acceleration in conceptus elongation. A combination of in vivo and in vitro experiments found that the effects of P4 on conceptus elongation are indirect and mediated through P4-induced effects in the endometrium. Despite effects on elongation, data on the effects of post-insemination supplementation with P4 on pregnancy rates are conflicting. This review highlights the effects of P4 on conceptus development and examines strategies that have been undertaken to manipulate P4 concentrations to increase fertility. [ABSTRACT FROM AUTHOR]

The aim of this research was to estimate the influence of environmental factors, such as air temperature and milk production, on reproduction traits of primiparous Polish Holstein-Friesian cows. The following reproduction traits were considered: interval from calving to first insemination, interval from first to last insemination, interval from calving to conception, number of inseminations per conception, first insemination conception rate and first insemination non-return rate. The impact of several measures describing the level of milk production and climate on fertility was examined using linear models. The model for each trait contained fixed effects of herd-year, month-year, age at calving and a random additive genetic effect. Deterioration of fertility due to an increase in peak milk yield was observed, e.g. elongation of the interval from the first to last insemination by 6 days as peak milk yield increased by 10 kg. It was found that temperature strongly affected reproduction. However, the results concerning the direction of that influence were inconsistent. An increase in temperature during the month of insemination had a negative effect on the length of the interval from the first to last insemination: elongation by 13 days along with an increase in temperature by 10°C. The opposite influence of an increase in temperature during the month of calving on the length of the interval from calving to the first insemination and on the length of the interval from calving to conception was observed: reduction by 8 days along with an increase in temperature by 10°C in both traits. The relationship of fertility with temperature and milk yield suggests the need to include these factors in the model used for genetic analysis of reproduction traits. [ABSTRACT FROM AUTHOR]

The aim of this research was to investigate the genetic relationship between reproduction traits and milk urea concentration (MU) during the first lactation of Polish Holstein-Friesian cows. The following reproduction traits were considered: interval from calving to first insemination, interval from first to last insemination, interval from calving to conception, number of inseminations to conception, first insemination conception rate and first insemination non-return rate to the 56th day. Data consisted of more than 1.2 million test-day records from 148,700 primiparous cows, for which fertility traits were available. Daily genetic correlations between MU and fertility traits were estimated with a random regression animal model. The Bayesian Gibbs sampling method was used to estimate the (co)variance components. Heritability of reproduction traits was low and ranged between 0.01 and 0.06. Heritability for MU was higher and relatively constant throughout the lactation (0.16-0.19). The genetic correlation between reproduction traits and MU in midlactation was close to zero, which suggests that MU measured close to the first insemination is of limited use in the indirect selection for fertility. Moderate genetic correlations between MU and reproduction traits, which were observed in the first two months of lactation, are sufficient for genetic improvement of fertility. However, better fertility was genetically related with higher MU, and an increase of MU concentration is undesirable. [ABSTRACT FROM AUTHOR]

Reproductive efficiency is a critical component of a sustainable cow-calf system. While several studies have identified factors underlying fertility, the genetic mechanisms contributing to this complex trait are still unclear. Our goal was to identify a set of predictive biomarker signatures from transcriptomics data associated with female cattle fertility. We implemented a multi-tiered approach using machine learning (ML) feature selection, gene co-expression network, and functional analysis. To this end, we retrieved public data from the Gene Expression Omnibus database (GEO GSE171577). The RNA-Seq data was generated from uterine luminal epithelial cells of recipient cows sampled on day four before embryo transfer. The data (n = 18 non-pregnant - NP and n = 25 pregnant - P) were analyzed using a standard pipeline based on FastQC, MultiQC, STAR, and DESeq2. Genes with expression values > 0.5 counts per million in 50% of the samples were filtered out. Feature and model selection was implemented through BioDiscML. Further, the PCIT algorithm was used to create gene co-expression networks from 15,039 genes kept after quality control. Our ML approach identified nine genes as predictors of pregnancy status. The genes included: SERPINE3, MRTFA, MEF2B, NAA16, ARHGEF7, PDCD1, FNDC1, ENSBTAG00000054585, and ENSBTAG00000019474. The networks from P and NP cows resulted in five and four thousand significantly co-expressed gene pairs, respectively. We then kept 1,837 pairs with a |r| > 0.7 and were co-expressed with the gene predictors from the ML analysis. Biological processes, such as vasculature development, oxidative phosphorylation, and focal adhesion were over-represented by genes from the P network. We identified immune system development, negative regulation of the biological process, and protein modification over-represented processes in the NP gene network. We have demonstrated the potential of combining different methods to identify fertility-related biomarkers and have provided insights into the complex genomic basis underlying pregnancy establishment in cattle. [ABSTRACT FROM AUTHOR]

• Rebreeding is one of the major challenges to improve the productive efficiency of Brazilian Nellore cows. • Consecutive rebreeding ability is as a new multi-categorical trait associated to the female fertility. • Consecutive rebreeding ability is a feasible indicator of Nellore fertility for long-term selection. • Consecutive rebreeding ability has high genetic association with stayability. Stayability(STAY) plays a substantial role in Nellore breeding programs in Brazil, but it does not differentiate cows with different rebreeding successes. Thus, we propose consecutive rebreeding ability (CRA) as a new multi-categorical trait related to the capacity of consecutive parturitions at calving intervals of less than 14 months. The heritability for CRA and its genetic correlations with stayability at 52 (STAY52) and 76 (STAY76) months, rib eye area (REA), subcutaneous backfat thickness (BF), age at first calving (AFC), post-yearling scrotal circumference (PSC), and post-yearling weight (PW) were estimated. The pedigree information provided a genealogical relationship matrix that contained 2,042,151 animals. The genetic parameters were estimated by multiple-trait Bayesian inference using the THRGIBBS1F90 software. The heritability estimates (posterior means and posterior standard deviations) for CRA, STAY52, STAY76, REA, BF, PW, AFC and PSC were, respectively, 0.11 (0.036), 0.092 (0.009), 0.15 (0.013), 0.35 (0.015), 0.13 (0.013), 0.34 (0.012), 0.17 (0.005) and 0.41 (0.021). In general, for a proposed trait (such as CRA) be considered as a replacement for existing ones, then it must be able to significantly increase the rate of genetic progress, that is a function of genetic variation, selection intensity and generation interval. Thus, the current STAY76 remains the most appropriate criterion for Nellore breeding programs. In this context, STAY76 still being recommended as a simple and practical trait for long-term Nellore cow selection. Additionally, the genetic association for CRA would not have a negative genetic impact on subcutaneous backfat thickness (BF), age at first calving (AFC) and post-yearling scrotal circumference (PSC). [ABSTRACT FROM AUTHOR]

Simple Summary: During the first weeks of lactation, dairy cows typically experience negative energy balance, leading to the mobilization of energy reserves. This predisposes early lactating cows towards metabolic diseases, such as fatty liver syndrome and ketosis. The supplementation of rumen-protected choline (RPC) is a strategy to restrict negative effects associated with negative energy balance in early lactating cows, but reported effects are inconsistent. This meta-analysis revealed that the supplementation of RPC positively affected dry matter intake, but this effect was associated with increased milk yield, thus without improving energy balance and metabolic profile of the cows. After parturition, cows undergo negative energy balance leading to fat mobilization, predisposing them to fatty liver syndrome and ketosis with major consequences for health and reproduction. Supplementation of rumen-protected choline (RPC) has attracted major research efforts during the last decade, assuming that choline improves liver function by increasing very low-density lipoprotein exportation from the liver, thereby improving metabolic profiles, milk production, and reproduction. However, the effects of RPC on production, health, and reproduction have been inconsistent. Therefore, the aim of this meta-analysis was to evaluate the effects of RPC supplementation, starting from d 20 (± 12.2) ante partum to d 53 (± 31.0) postpartum, on feed intake, milk production performance and metabolic profiles of dairy cows early postpartum. Data analyses from 27 published studies showed an increase in postpartal dry matter intake (from on average 19.1 to 19.9 kg/d; p < 0.01) and milk yield (from on average 31.8 to 32.9 kg/d; p = 0.03) in cows receiving RPC. Milk fat yield and milk protein yield were also increased (p ≤ 0.05), without changing milk protein and fat contents. However, no interactive effects between cow's milk yield level and RPC-supplementation as well as no dose-dependent effects of RPC supplementation were observed. Supplementing the diet with RPC showed no effects on blood metabolites (non-esterified fatty acids, beta-hydroxybutyrate, glucose, and cholesterol), independent of the milk yield level of the cows. An effect on liver triacylglycerol contents, incidence of ketosis, and mastitis could not be confirmed across all studies included in this meta-analysis. Also, the positive effects of RPC supplementation on reproductive performance were not consistent findings. In conclusion, supplementing RPC in lactating dairy cows showed positive effects on dry matter intake which likely caused the improved milk yield. However, RPC supplementation did not improve the metabolic health status of the cows. As several factors might be related to the responses to RPC, further research is needed to explore the precise mechanisms of RPC action in lactating cows, especially with regards to feed intake improvement and its related metabolic health-promoting potential in early lactating dairy cows. [ABSTRACT FROM AUTHOR]

Transition is a stressful period and critical for the entire cow's productive lifespan and reproduction. Optimal feeding management during transition period enables smooth metabolic adaptation to the initiation of lactation. Major nutritional challenge during this period is the urgent need to counteract the drastic deficits in energy and nutrients of the early-lactating cow. This is primarily done by inclusion of large amounts of concentrates in the diet during early lactation, causing major dietary imbalances with utmost importance for rumen health. Proper feeding management targeting rumen health in the transition period improves nutrient degradation and the net supply with energy and key nutrients of the host while preventing systemic disturbances and inflammation, events which are instrumental for cow's overall health and reproductive performance. The review provides insights into the role of, and gives practical hints regarding diet balancing efforts and feeding management strategies targeting rumen health and systemic inflammation during the periparturient period with the aim to enhance cow health and fertility., (Copyright © 2015 Elsevier Ltd. All rights reserved.)