Machine learning analysis to identify endometrial transcriptomic biomarkers predictive of pregnancy success following artificial insemination in dairy cows
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ABSTRACT:
PROVIDER: PRJNA1043136 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR26893100_1.fastq.gz | Fastqsanger.gz | |||
| SRR26893100_2.fastq.gz | Fastqsanger.gz | |||
| SRR26893200_1.fastq.gz | Fastqsanger.gz | |||
| SRR26893200_2.fastq.gz | Fastqsanger.gz | |||
| SRR26893101_1.fastq.gz | Fastqsanger.gz |
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Project description:The objective of this research was to identify a set of genes whose transcript abundance is predictive of a cow’s ability to become pregnant following artificial insemination (AI). Endometrial epithelial cells from the uterine body were collected for RNA sequencing using the cytobrush method from 193 first-service Holstein cows at estrus prior to AI (day 0). A group of 253 first-service cows not used for cytobrush collection were controls. There was no effect of cytobrush collection on pregnancy outcomes at day 30 or 70, or on pregnancy loss between day 30 and 70. There were 2 upregulated and 214 downregulated genes (FDR < 0.05, absolute fold change > 2-fold) for cows pregnant at day 30 versus those that were not pregnant. Functional terms overrepresented in the downregulated genes included those related to immune and inflammatory responses. Machine learning for fertility biomarkers with the R package BORUTA resulted in identification of 57 biomarkers that predicted pregnancy outcome at day 30 with an average accuracy of 77%. Thus, machine learning can identify predictive biomarkers of pregnancy in endometrium with high accuracy. Moreover, sampling of endometrial epithelium using the cytobrush can help understand functional characteristics of the endometrium at AI without compromising cow fertility.
2024-04-10 | GSE248266 | GEO
Project description:Infertility is a disease that affects humans and cattle in similar ways. The resemblance includes complex genetic architecture, multiple etiology, low heritability of fertility related traits in females, and the frequency in the female population. Here, we used cattle as a biomedical model to test the hypothesis that gene expression profiles of protein-coding genes expressed in peripheral white blood cells (PWBCs), and circulating micro RNAs in plasma, are associated with female fertility, measured by pregnancy outcome. We drew blood samples from 17 female calves on the day of artificial insemination and analyzed transcript abundance for 10496 genes in PWBCs and 290 circulating micro RNAs. The females were later classified as pregnant to artificial insemination, pregnant to natural breeding or not pregnant. We identified 1860 genes producing significant differential coexpression (eFDR<0.002) based on pregnancy outcome. Additionally, 237 micro RNAs and 2274 genes in PWBCs presented differential coexpression based on pregnancy outcome. Furthermore, using a machine learning prediction algorithm we detected a subset of genes whose abundance could be used for blind categorization of pregnancy outcome. Our results provide strong evidence that bloodborne transcript abundance is highly associated with fertility in females.
2020-02-28 | GSE146041 | GEO
Project description:Two experiments investigated the effects of supplementing Ca salts of soybean oil (CSSO) during early gestation on reproductive function and pregnancy rates to AI in Bos taurus beef cows. In Exp. 1, 771 suckled, lactating, multiparous Angus cows were divided into 22 groups of approximately 35 cows per group and timed inseminated on day 0. After AI, groups were assigned randomly to receive (as-fed basis) 100 g of ground corn + 100 g of soybean meal per cow/d, in addition to 1) 100 g/cow daily of CSSO (n = 11) or 2) 87 g of prilled saturated fat + 13 g of limestone per cow/d (CON; n = 11). Groups were maintained in individual tall fescue-dominated pastures and offered treatments from day 0 to 21. Pregnancy status was determined between days 45 and 55 via transrectal ultrasonography. Cows receiving CSSO had greater (P = 0.01) pregnancy rates to timed AI compared with CON (60.2 vs. 51.7%; SEM = 4.2). In Exp. 2, 90 suckled, lactating, multiparous Angus × Hereford cows housed in 18 drylot pens (5 cows per pen) were assigned to the same timed AI program and treatments from Exp. 1 (9 pens per treatment) and received 20 kg/d (DM basis) of grass-alfalfa hay. Transrectal ultrasonography was performed to verify ovulation and corpus luteum (CL) volume before AI (day 0), on days 7 and 15. After ultrasonography on day 15, cows diagnosed without a CL on day 0, but with a CL greater than 0.38 cm3 in volume on days 7 and 15 (2 or 3 cows per pen; CSSO, n = 20; CON, n = 24), were assigned to conceptus collection via transcervical flushing and endometrial biopsy in the uterine horn ipsilateral to the CL. Blood samples were collected for FA analysis on days 0, 7, and 15. Blood was collected from cows not assigned to conceptus collection for whole-blood RNA extraction on day 20 and for pregnancy diagnosis on day 30 by measuring concentrations of pregnancy-associated glycoproteins. Cows receiving CSSO had greater (P ≤ 0.04) mean plasma concentrations of linoleic acid and ω-6 FA compared with CON on days 7 and 15. Moreover, CSSO supplementation increased (P = 0.05) mRNA expression of interferon-tau by the conceptus and blood mRNA expression of interferon-stimulated gene 15 and 20,50-oligoadenylate synthetase on day 20 in gestating cows. Hence, post-AI CSSO supplementation to B. taurus beef cows improved pregnancy rates to timed AI, which can be associated with increased mRNA expression of interferon-tau by the conceptus when CSSO is supplemented during early gestation.
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Project description:The aim of the study was to compare the morphometric features of sperm head size and shape from the Pietrain line and the Duroc × Pietrain boar crossbred terminal lines, and to evaluate their relationship with reproductive success after artificial insemination of sows produced from crossbreeding the York, Landrace and Pietrain breeds. Semen samples were collected from 11 sexually mature boars. Only ejaculates with greater than 70% motility rate and <15% of abnormal sperm were used for artificial inseminations (AI) and included in the study. Samples were analyzed using an ISAS®v1 computer-assisted sperm analysis system for eight morphometric parameters of head shape and size (CASA-Morph). Sub-populations of morphometric ejaculates were characterized using multivariate procedures, such as principal component (PC) analysis and clustering methods (k-means model). Four different ejaculate sub-populations were identified from two PCs that involved the head shape and size of the spermatozoa. The discriminant ability of the different morphometric sperm variables to predict sow litter size was analyzed using a receiver operating characteristics (ROC) curve analysis. Sperm head length, ellipticity, elongation, and regularity showed significant predictive capacity on litter size (0.59, 0.59, 0.60, and 0.56 area under curve (AUC), respectively). The morphometric sperm sub-populations were not related to sow litter size.
| S-EPMC8064074 | biostudies-literature
Project description:The objective was to assess the effect of housing conditions during the summer months on the success rates of cervical artificial insemination (AI) with cooled semen, in intensively reared dairy ewes in Greece. The study involved 2083 Lacaune ewes from 23 flocks that were serviced during May to September. An estrous synchronization protocol with the insertion of progestogen sponges for 14 days and eCG administration at sponge removal, was used. All ewes were inseminated 54-57 h after sponge removal with cooled semen (15 °C) from 10 Lacaune rams. Pregnancy diagnosis was performed via trans-dermal ultrasonography at 35-40 days after AI. Data recording started the day after sponge placement (15 days prior to AI), and lasted up to 14 days after AI. Daily records included temperature, relative humidity, and Temperature-Humidity Index (THI) inside the shed. Available space and volume per animal, frequency of bedding renewal, access to a yard, and indoor light were also recorded in each farm. Binary logistic regression of data records showed that temperature and THI increases at days -15 to +4 around AI (day 0) had a negative effect on pregnancy rates (reducing the likelihood of pregnancy by 3-6% and 7%, respectively). The latter also decreased significantly (p < 0.05) in farms with high stocking density, non-frequent bedding renewal, and outdoor access by ewes (by 30%, 34%, and 44%, respectively). Overall, the results indicate that appropriate housing conditions are warranted to increase the success of AI in dairy ewes during the summer months.
| S-EPMC9559479 | biostudies-literature
Project description:Sequencing of commercial boar semen use in artificial insemination
| PRJEB51770 | ENA
Project description:The deterioration in reproductive performance in association with low fertility leads to significant economic losses on dairy farms. The uterine microbiota has begun to attract attention as a possible cause of unexplained low fertility. We analyzed the uterine microbiota associated with fertility by 16S rRNA gene amplicon sequencing in dairy cows. First, the alpha (Chao1 and Shannon) and beta (unweighted and weighted UniFrac) diversities of 69 cows at four dairy farms that had passed the voluntary waiting period before the first artificial insemination (AI) were analyzed with respect to factors including farm, housing style, feeding management, parity, and AI frequency to conception. Significant differences were observed in the farm, housing style, and feeding management, except parity and AI frequency to conception. The other diversity metrics did not show significant differences in the tested factors. Similar results were obtained for the predicted functional profile. Next, the microbial diversity analysis of 31 cows at a single farm using weighted UniFrac distance matrices revealed a correlation with AI frequency to conception but not with parity. In correlation with AI frequency to conception, the predicted function profile appeared to be slightly modified and a single bacterial taxon, Arcobacter, was detected. The bacterial associations related to fertility were estimated. Considering these, the uterine microbiota in dairy cows can be varied depending on the farm management practices and may become one of the measures for low fertility. IMPORTANCE We examined the uterine microbiota associated with low fertility in dairy cows derived from four commercial farms via a metataxonomic approach using endometrial tissues prior to the first artificial insemination. The present study provided two new insights into the relevance of uterine microbiota with respect to fertility. First, the uterine microbiota varied depending on housing style and feeding management. Next, a subtle change was observed in functional profile analysis: a formation of uterine microbiota was detected to be different in correlation with fertility in one farm studied. Considering these insights, an examination system on bovine uterine microbiota is hopefully established based on continuous research on this topic.
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Project description:Mating is fundamental to the success and reproduction of most organisms, although the physiological and transcriptional changes associated with this process have been largely characterized only in Drosophila. In this study, we use honey bees as a model system since their queens undergo massive and permanent physiological and behavioral changes following mating. Previous studies have identified changes associated with the transition from a virgin queen to a fully-mated, egg-laying queen. Here, we further uncouple the mating process to examine the effects of natural mating vs. instrumental insemination and saline vs. semen insemination. We observed significant overlap between our study and analogous studies in Drosophila, suggesting that some post-mating mechanisms are conserved across insect orders.
2009-12-01 | E-MEXP-2205 | biostudies-arrayexpress
Project description:BackgroundA retrospective cohort study using a 10 year artificial insemination (AI) and cow reproductive performance data was conducted to study the success rate of AI; associations between effectiveness of AI and breed, AI season and, number of service per conception, and economic impact of failure of FSC in Dessie town, Dessie zuria and Kutaber districts. A total of 3480 dairy cows' AI and reproductive performance records which were performed between 2003 and 2013 in the three selected districts of South Wollo were used. The economic losses and costs for cows that failed to conceive at their first AI associated with the larger number of days open were estimated.ResultThe prevalence of conception has a statistically significant difference between breeds of cows (P = 0.019). The non-return rate for first service was 58.54%. The median days to first service (DFS), inter-service interval (ISI) and gestation length (GL) were 126, 30 and 278 days respectively. Whereas, the mean + SD days open, calving interval (CI), number of inseminations (NOI) and number of services per conception (NSPC) were 147.2 ± 60.26, 424.5 ± 60.55, 1.14 ± 0.38 and 1.15 ± 0.39 respectively. Based on AI season there was a significant difference in conception between winter and spring (P = 0.021). There is a 45.04 days extension in the mean calving to conception interval in cows that did not conceive at their first AI but conceived by 2nd and 3rd AI than in cows that did conceive at their first AI. A total of 21,665.3 ETB extra costs was spent on reproductive treatment and other management for cows that failed to conceive at their first AI but conceived by second and third service. In cows that did not conceive totally the owner losses on average 473.7 ETB per cow per day extra costs until the cows will be culled.ConclusionTherefore to increase the conception rate and decrease the economic loss the owners of the dairy cows should supervise the cows regularly and should be trained on how to identify cows on estrous, the AI technicians should be trained to conduct the AI service accurately.
| S-EPMC9199250 | biostudies-literature
Project description:In asses, semen collection, cryopreservation, and artificial insemination (AI) with frozen-thawed semen have been scarcely described and success rate, particularly following AI, is reportedly low. In the absence of reliable protocols, assisted reproductive technologies cannot support the conservation efforts aimed at endangered wild ass species and domestic donkey breeds. Two experiments were conducted in this study. In experiment 1 we evaluated freezing Abyssinian donkey (N = 5, 4 ejaculates each) spermatozoa using three freezing extenders (Berliner Cryomedium + glycerol, BC+G; BotuCrio, BOTU; INRAFreeze, INRA) and two cryopreservation techniques (liquid nitrogen vapour, LNV; directional freezing, DF). Post-thaw evaluation indicated that BOTU and INRA were similar and both superior to BC+G (P ≤ 0.004 for all motility tests), and that DF was superior to LNV (P < 0.002 for all evaluation parameters). In experiment 2, relying on these results, we used Abyssinian donkey sperm frozen in BOTU and INRA by DF for AI (N = 20). Prior to AI, thawed samples were diluted in corresponding centrifugation media or autologous seminal fluids at 1:1 ratio. No difference was found between BOTU and INRA or between the addition of seminal fluids or media, all resulting in ~50% pregnancy, and no differences were noted between males (N = 4). The size of pre-ovulatory follicle was a significant (P = 0.001) predictor for AI success with 9/10 pregnancies occurring when follicular size ranged between 33.1-37.4 mm, no pregnancy when it was smaller, and only one when larger. A number of ass species face the risk of extinction. Knowledge gained in this study on the Abyssinian donkey can be customised and transferred to its closely related endangered species and breeds.
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