RESUMO
The objective 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. Functional characteristics of the genes comprising the set of biomarkers is indicative that a major determinant of cow fertility, at least for first insemination after calving, is immune status of the uterus, which, in turn, is likely to reflect the previous history of uterine disease.
RESUMO
BACKGROUND: In beef cattle, more than 50% of the energy input to produce a unit of beef is consumed by the female that produced the calf. Development of genomic tools to identify females with high genetic merit for reproductive function could increase the profitability and sustainability of beef production. RESULTS: Genome-wide association studies (GWAS) were performed using a single-step genomic best linear unbiased prediction approach on pregnancy outcome traits from a population of Angus-Brahman crossbred heifers. Furthermore, a validation GWAS was performed using data from another farm. Heifers were genotyped with the Bovine GGP F250 array that contains 221,077 SNPs. In the discovery population, heifers were bred in winter breeding seasons involving a single round of timed artificial insemination (AI) followed by natural mating for 3 months. Two phenotypes were analyzed: pregnancy outcome to first-service AI (PAI; n = 1,481) and pregnancy status at the end of the breeding season (PEBS; n = 1,725). The heritability was estimated as 0.149 and 0.122 for PAI and PEBS, respectively. In the PAI model, one quantitative trait locus (QTL), located between 52.3 and 52.5 Mb on BTA7, explained about 3% of the genetic variation, in a region containing a cluster of γ-protocadherin genes and SLC25A2. Other QTLs explaining between 0.5% and 1% of the genetic variation were found on BTA12 and 25. In the PEBS model, a large QTL on BTA7 was synonymous with the QTL for PAI, with minor QTLs located on BTA5, 9, 10, 11, 19, and 20. The validation population for pregnancy status at the end of the breeding season were Angus-Brahman crossbred heifers bred by natural mating. In concordance with the discovery population, the large QTL on BTA7 and QTLs on BTA10 and 12 were identified. CONCLUSIONS: In summary, QTLs and candidate SNPs identified were associated with pregnancy outcomes in beef heifers, including a large QTL associated with a group of protocadherin genes. Confirmation of these associations with larger populations could lead to the development of genomic predictions of reproductive function in beef cattle. Moreover, additional research is warranted to study the function of candidate genes associated with QTLs.
RESUMO
The objectives of the present study were to characterize the expression of genes encoding for cell signaling ligands in the bovine endosalpinx and endometrium and analyze spatial changes in gene expression. RNA sequencing was performed for the endosalpinx from the ampulla of the oviduct and endometrium from the upper and middle uterine horn and uterine body at day 2 after ovulation from ipsilateral and contralateral sides relative to the ovulatory ovary. Of the 17,827 unique mRNA transcripts mapped, 2,072 were affected by cranial-caudal position in the reproductive tract and 818 were affected by side (false discovery rate < 0.05). There were 334 genes encoding for cell signaling ligands, with 128 genes having greater than two transcripts per million on average. A total of 81 cell signaling ligand genes were affected by position and 24 were affected by side. A data set of the transcriptome of two to four cell embryos was used to identify cell signaling ligand genes that were highly expressed in the ampulla for which there was high expression of the receptor in the embryo. The most expressed ligand-receptor pairs were PSAP/SORT1, MIF/CXCR4, GPI/AMFR, and KITLG/KIT. These cell signaling ligands, as well as others whose gene is expressed in the endosalpinx and endometrium, may influence early embryonic development. Spatial changes throughout the reproductive tract highlight the distinctive expression profile of the oviduct versus the endometrium, including a set of the identified genes encoding for cell signaling ligands, and highlight the local influence of the ovary. The results also show the continuity of expression for large numbers of genes in the reproductive tract.NEW & NOTEWORTHY Examination of the transcriptome of the endosalpinx and endometrium revealed the degree to which gene expression in the reproductive tract varies spatially. The expression of genes encoding cell signaling molecules that could potentially regulate embryonic development was also identified.
