Heat stress affects the granulosa cells (GCs) and ovarian follicular microenvironment, causing poor oocyte developmental competence and fertility. This study aimed to investigate the physical responses and global transcriptomic changes in bovine GCs to acute heat stress (43 ℃ for 2 h) in-vitro and gave essential insights into the general interaction at cell–stress nexus. Heat-stressed GCs exhibited transient proliferation senescence, resumed proliferation at 48 h post-stress. While post-stress immediate culture-media change had a relatively positive effect on proliferation resumption. Increased accumulation of reactive oxygen species and apoptosis was observed in heat stress group. In spite of the upregulation of pro-apoptotic and caspase executioner genes, antioxidants and anti-apoptotic genes were also upregulated in heat-stressed GCs. Progesterone and Estrogen hormones along with steroidogenic genes expression, declined significantly, in spite of the upregulation of genes involved in cholesterol synthesis. Out of 12385 differentially expressed genes (DEGs), 330 significant DEGs (75 upregulated, 225 downregulated) were subjected to KEGG functional pathway annotation, gene ontology enrichment, and STRING network analyses. Based on the manual query of DEGs, pathway and enrichment analyses, a vast interplay observed among all major signaling pathways strongly evidence the repression of cellular transcriptional and proliferation activity, averting the effects of heat stress through remodeling of cellular structural proteins and energetic-homeostasis. This study presents detailed responses of acute heat-stressed GCs at physical, transcriptional, and pathway levels and presents interesting insights into future studies regarding GCs adaptation and their interaction with oocyte and reproductive system at ovarian level.

Previous studies reported the physical, transcriptomics and metabolomics changes in in-vitro acute heat stressed bovine granulosa cells. Granulosa cells exhibited transient proliferation senescence, oxidative stress, increased rate of apoptosis, and decline in steroidogenic activity. This study performs joint integration and network analysis of metabolomics and transcriptomics data to further narrow down and elucidate the role of differentially expressed genes, important metab-olites and relevant cellular and metabolic pathways in acute heat-stressed granulosa cells. Among significant (Raw P-value <0.05) metabolic pathways where metabolites and genes did converge, this study found Vitamin B6 metabolism, Glycine, serine and threonine metabolism, Phenylalanine metabo-lism, Arginine biosynthesis, Tryptophan metabolism, Arginine and proline metabolism, Histidine metabolism, and Glyoxylate and dicarboxylate metabolism. Important significant convergent bio-logical pathways included, ABC transporters and Protein digestion and absorption, while func-tional signaling pathways included cAMP, mTOR, and AMPK signaling pathways together with Ovarian steroidogenesis pathway. Among caner pathways, the most important pathway was Central carbon metabolism in cancer. Through multiple analysis query, Progesterone, Serotonin, citric acid, Pyridoxal, L-Lysine, Succinic acid, L-Glutamine, L-Leucine, L-Threonine, L-Tyrosine, Vitamin B6, Choline, and CYP1B1, MAOB, VEGFA, WNT11, AOX1, ADCY2, ICAM1, PYGM, SLC2A4, SLC16A3, HSD11B2 and NOS2 appeared to be important enriched metabolites and genes, respectively. These genes, metabolites, metabolic, cellular and cell signaling pathways com-prehensively elucidate the mechanisms underlying the intricate fight between death and survival in acute heat-stressed bovine granulosa cells, and essentially help further our understanding and future quest of research in this direction.

The molecular mechanisms underlying heat stress tolerance in animals to high temperatures remain unclear. This experiment was performed with Sprague-Dawley rats housed at 22 ℃ (control group; CT), and 42 ℃ for 30 min (H30), 60 min (H60), and 120 min (H120). Transcriptomic analysis using RNA-Sequencing (RNA-Seq) from blood (CT and H120), liver (CT, H30, H60, and H120), and adrenal glands (CT, H30, H60, and H120) was performed. The differentially expressed mRNA isoforms (DEIs) were identified and annotated by the CLC Genomics Workbench. Biological process and metabolic pathway analyses were performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) database. A total of 225, 5,764, and 4,988 DEIs in the blood, liver, and adrenal glands were observed. Furthermore, the number of novel differentially expressed transcript lengths with annotated genes and the novel differentially expressed transcript with non-annotated genes were 136 and 8 in blood, 3,549 and 120 in the liver, as well as 3,078 and 220 in adrenal glands, respectively. A total of 35 genes were involved in the heat stress response, out of which Dnaja1, LOC680121, Chordc1, AABR07011951.1, Hsp90aa1, Hspa1b, Cdkn1a, Hmox1, Bag3 and Dnaja4 were commonly identified in the liver and adrenal glands, suggesting that these genes may regulate heat stress response through interactions between liver and adrenal glands. The results suggest that the identified mRNA isoforms could be considered as potential candidates for selecting mammals to improve thermotolerance.

Milk MIR spectra have been shown to provide valuable information on a wide range of traits to be used in dairy cattle breeding programs. Selecting the most informative variables from complex data can improve prediction accuracy and model robustness and, consequently, the interpretability of MIR spectra. Thus, we aimed to investigate the prediction performance of feature selection methods based on MIR spectra data, using the milk fatty acid (FA) profile as an example to illustrate the evaluated procedure. Data of MIR spectra, milk test-day records, and reference FA concentrations of 155 first-parity Holstein cows were used in the analyses. Four models comprising different explanatory variables and five feature selection methods were evaluated. The results indicated that the Competitive Adaptive Reweighted Sampling (CARS) method can effectively select the most informative variables from the MIR spectra, resulting in higher prediction accuracies than other variable selection approaches. The model including selected MIR spectra and cow information variables [days in milk at the test day, age at the test day, pregnancy stage (in days), number of days open, number of inseminations, and somatic cell count] yielded the best FA profile predictions based on Partial Least Square regression. In particular, ten FAs (C8:0, C10:0, C14:1, C17:0 isomers, C18:1, C18:1 isomer, medium-chain FA, unsaturation FA, monounsaturated FA, and polyunsaturated FA) presented accuracies based on the determination coefficient (R2cv) ranging from 0.66 to 0.85 in internal validation and from 0.65 to 0.84 in external validation. By running CARS 1,000 times in internal validations, we obtained the frequency of selected milk MIR wavenumber for 35 FAs. The most related wavenumbers to FAs were found within 1,003 to 1,145 cm-1, while other discrete areas were between 1,651 to 1,797 and 2,834 to 2,954 cm-1. These biomarkers may give insights into the relationship between MIR spectra and FA phenotypes. In conclusion, using CARS and cow information improved predictions of FAs based on MIR spectra in Chinese Holstein dairy cows. Additional validation studies should be conducted as larger datasets become available.

To study the oil and gas distribution law in the slope area of the hydrocarbon-bearing basin, the distribution of the effective dominant path of sand bodies transporting oil and gas is a fundamental subject. In this paper, we introduced an effective way to predict such transport paths and applied the method to study the sand bodies of the lower first member of the Shahejie Formation (E3s1L) in the southern area of the Qikou Depression in the Bohai Bay Basin (Qinan). We first define the dominant hydrocarbon transport paths of the sand body as the superimposed area of the contiguously distributed area of the sand body and the paleotectonic ridges at the top of the formation where the sand body is located. Then we define the oil and gas supply area of the oil source fault as the overlapped area of the favorable transport path of oil source faults and the width of the associated fracture zone. Stacking the two areas, we can delineate the distribution of the effective dominant transport paths of the sand bodies. The results from our case study of the Qinan area show that the effective dominant paths of sand bodies transporting oil and gas in the E3s1L Formation in the Qinan area are distributed throughout the region with better development in the west than in the east. The paths in the eastern part extend from north to south, while the paths in the western part extend from northeast to southwest, which is favorable for the convergence of oil and gas generated from the source rocks of the third member of Shahejie Formation (Es3) in the Northeastern main depression of Qikou and the formation of oil and gas accumulations in the l E3s1L Formation. The results are consistent with the fact that oil and gas discovered in the E3s1L Formation in the Qinan region are mainly distributed in the central and western regions, with a small amount in the southeast. Therefore, the suggested method is feasible to predict the effective dominant path of sand bodies transporting oil and gas.