A near complete genome assembly of the East Friesian sheep genome.

Advancements in sequencing have enabled the assembly of numerous sheep genomes, significantly advancing our understanding of the link between genetic variation and phenotypic traits. However, the genome of East Friesian sheep (Ostfriesisches Milchschaf), a key high-yield milk breed, remains to be fully assembled. Here, we constructed a near-complete and gap-free East Friesian genome assembly using PacBio HiFi, ultra-long ONT and Hi-C sequencing. The resulting genome assembly spans approximately 2.96 Gb, with a contig N50 length of 104.1 Mb and only 164 unplaced sequences. Remarkably, our assembly has captured 41 telomeres and 24 centromeres. The assembled sequence is of high quality on completeness (BUSCO score: 97.1%) and correctness (QV: 69.1). In addition, a total of 24,580 protein-coding genes were predicted, of which 97.2% (23,891) carried at least one conserved functional domain. Collectively, this assembly provides not only a near T2T gap-free genome, but also provides a valuable genetic resource for comparative genome studies of sheep and will serve as an important tool for the sheep research community.

Machine learning approach for predicting post-intubation hemodynamic instability (PIHI) index values: towards enhanced perioperative anesthesia quality and safety.

BACKGROUND: Adequate preoperative evaluation of the post-intubation hemodynamic instability (PIHI) is crucial for accurate risk assessment and efficient anesthesia management. However, the incorporation of this evaluation within a predictive framework have been insufficiently addressed and executed. This study aims to developed a machine learning approach for preoperatively and precisely predicting the PIHI index values. METHODS: In this retrospective study, the valid features were collected from 23,305 adult surgical patients at Peking Union Medical College Hospital between 2012 and 2020. Three hemodynamic response sequences including systolic pressure, diastolic pressure and heart rate, were utilized to design the post-intubation hemodynamic instability (PIHI) index by computing the integrated coefficient of variation (ICV) values. Different types of machine learning models were constructed to predict the ICV values, leveraging preoperative patient information and initiatory drug infusion. The models were trained and cross-validated based on balanced data using the SMOTETomek technique, and their performance was evaluated according to the mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE) and R-squared index (R2). RESULTS: The ICV values were proved to be consistent with the anesthetists' ratings with Spearman correlation coefficient of 0.877 (P < 0.001), affirming its capability to effectively capture the PIHI variations. The extra tree regression model outperformed the other models in predicting the ICV values with the smallest MAE (0.0512, 95% CI: 0.0511-0.0513), RMSE (0.0792, 95% CI: 0.0790-0.0794), and MAPE (0.2086, 95% CI: 0.2077-0.2095) and the largest R2 (0.9047, 95% CI: 0.9043-0.9052). It was found that the features of age and preoperative hemodynamic status were the most important features for accurately predicting the ICV values. CONCLUSIONS: Our results demonstrate the potential of the machine learning approach in predicting PIHI index values, thereby preoperatively informing anesthetists the possible anesthetic risk and enabling the implementation of individualized and precise anesthesia interventions.

Community Synergy of Lactic Acid Bacteria and Cleaner Fermentation of Oat Silage Prepared with a Multispecies Microbial Inoculant.

To investigate community synergy of lactic acid bacteria (LAB) and cleaner fermentation of oat silage, oat silages were prepared with or without (control) commercial LAB inoculants LI1 (containing Lactiplantibacillus plantarum, Lentilactobacillus buchneri, Lacticaseibacillus paracasei, and Pediococcus acidilactici) and LI2 (containing Lactiplantibacillus plantarum and Lentilactobacillus buchneri). The microbial community, LAB synergy, and cleaner fermentation were analyzed at 1, 3, 6, 15, 35, and 90 days of ensiling. The LAB inoculant improved fermentation quality, with significantly (P < 0.05) lower pH, ammonia nitrogen content, and gas production and higher lactic acid and acetic acid contents than those of the control. Enterobacteriaceae was the main bacterial community in early stage of fermentation, which utilizes sugar to produce CO2 gas, causing dry matter (DM) and energy loss. As fermentation progressed, the microbial diversity decreased, and the microbial community shifted from Gram-negative to Gram-positive bacteria. The inoculation of multispecies LAB displayed community synergy; Pediococcus acidilactici formed a dominant community in the early stage of fermentation, which produced an acid and anaerobic environment for the subsequent growth of Lentilactobacillus and Lacticaseibacillus species, thus forming a LAB-dominated microbial community. The predicted functional profile indicated that the silage inoculated with LI1 enhanced the carbohydrate metabolism pathway but inhibited the amino acid metabolism pathway, which played a role in promoting faster lactic acid production, reducing the decomposition of protein to ammonia nitrogen, and improving the fermentation quality of silage. Therefore, oat silage can be processed to high-quality and cleaner fermented feed by using an LAB inoculant, and LI1 showed better efficiency than LI2. IMPORTANCE Oat natural silage is rich in Enterobacteriaceae, increasing gas production and fermentation loss. Lactic acid bacteria interact synergistically to form a dominant community during ensiling. Pediococci grow vigorously in the early stage of fermentation and create an anaerobic environment. Lactobacilli inhibit the harmful microorganisms and result in cleaner fermentation of oat silage.

Identification of piRNAs in the testes of Sunite and Small-tailed Han sheep.

P-element-induced wimpy testis-interacting RNAs (piRNAs) are small RNAs that are essential for mammalian spermatogenesis and testicular development. Comparative analyses of the molecular mechanisms of spermatogenesis among different organisms are therefore dependent on accurate piRNA characterizations. In this study, we identified piRNAs in the testes of two breeds of Mongolian sheep: the Sunite (SN), which has a low reproductive rate, and Small-tailed Han (STH), which has a high reproductive rate. A thorough understanding of the mechanisms underlying the differences in fecundity between the two breeds might provide insights for the improvement of fertility and reproductive success in these and other sheep breeds. We identified 835 piRNAs and 206 piRNA clusters across the two breeds. Of these, 29 putative piRNAs were expressed in the SN samples only, and 229 putative piRNAs were expressed in the STH samples only. In addition, 206 piRNA clusters were upregulated in STH sheep as compared to the SN sheep. Functional pathway analysis indicated that the genes neighboring the predicted piRNAs were likely associated with spermatogenesis. piRNAs might thus be linked to male fecundity in sheep. Our results increase knowledge of the association between piRNAs and male fertility.