Resultados de investigación

Additional file 12: Supplementary Table S3. METTL1 bound RNAs in HEK293T cells., Consejo Superior de Investigaciones Científicas (España), Peer reviewed

Additional file 13: Supplementary Table S4. tRNA fragment reads in Control (wt) and METTL1 KO cells., Consejo Superior de Investigaciones Científicas (España), Peer reviewed

Additional file 14: Supplementary Table S5. Differentially synthesised nascent peptides in WT and METTL1 KO PC3 cells., Consejo Superior de Investigaciones Científicas (España), Peer reviewed

5 tables, Supplementary Material for the article https://doi.org/10.3390/microorganisms8081121, Table S1. Basic biochemical composition of fish peptones (mean values±confidence intervals).-- Table S2. Composition of culture media for marine probiotic bacteria (g/L).-- Table S3. Numerical values and confidence intervals for parameters obtained from experimental data of Pseudomonas fluorescens (Pf) growths modelled by logistic equation (1-4).-- Table S4. Continued table 3.-- Table S5. Costs of production of biomass and viable cells in the commercial marine medium and in the media formulated with fish peptones and seawater, Peer reviewed

Additional file 15: Supplementary Table S6. Differentially expressed proteins in WT and METTL1 KO PC3 cells., Consejo Superior de Investigaciones Científicas (España), Peer reviewed

Additional file 16: Supplementary Table S7. Differentially expressed mRNAs in WT vs METTL1 KO PC3 cells., Peer reviewed

7 datasets, This data set contains the stable isotope record of Uvigerina auberiana, Melonis barleeanus and Cibicidoides spp., abundance and fragmentation of planktonic foraminifera, major and trace elements and total inorganic carbon content of ODP Site 202-1242, Peer reviewed

Additional file 17: Supplementary Table S8. Correlation of differentially expressed mRNAs and newly synthesized proteins in WT and METTL1 KO PC3 cells., Consejo Superior de Investigaciones Científicas (España), Peer reviewed

Additional file 18. Graphical abstract., Consejo Superior de Investigaciones Científicas (España), Peer reviewed

Supplementary tables to the manuscript entitled Assessment of milk metabolites as biomarkers for predicting feed efficiency in dairy sheep, Supplemental Table 1: Grids used in the hyperparameter tuning stage for each machine learning (ML) model. Supplemental Table 2: Summary of milk production and FE phenotypes in the 39 Assaf ewes analyzed in this work. For each animal (Sample_ID), the type of lambing (single or twins), the means (±coefficient of variation in %) of the milk production traits: milk yield (MY), milk protein percentage (PP), milk fat percentage (FP) and milk lactose percentage (LC) are presented. The FE parameters recorded during the three-week evaluation period: Dry matter intake (DMI), feed efficiency indices RFI and FCR and the high, medium or low-efficiency group for each FE-index are also presented. Supplemental Table 3: m/z and LC retention time (RT, min) for the features identified in the raw milk metabolomic signature for the 39 Assaf ewes. The four sheets show the results of the reversed-phase liquid chromatography (C8) and hydrophilic interaction liquid chromatography (HILIC) for the positive and negative poles, respectively. Supplemental Table 4: Selected features for residual feed intake (RFI) and feed conversion ratio (FCR) based on the Variable Importance in the Projection (VIP) values obtained in the partial least squares discriminant analysis. Supplemental Table 5: Results of the hyperparameter tunning stage for the 100 iterations of random assignment of samples in the train and training population for all machine learning models applied for both feed efficiency (FE) metrics, residual feed intake (RFI) and feed conversion ratio (FCR). The different sheets show the results of the four ML methods used (multi-layer feedforward artificial neural network (Deep), Randon Forest (RF), extreme gradient boosting (xgboost) and Support Vector Machine (SVM) using all features (All) and those selected by VIP. Supplemental Table 6: Candidate compounds annotated for the 41 and 26 features selected for residual feed intake (RFI) and feed conversion ratio (FCR) during the partial least squares discriminant analysis for the discrimination of the feed efficiency (FE) groups. Supplemental Table 7: Results of metabolic pathways enrichment analysis obtained using IMPaLA software for the candidate compound matches obtained during the annotation process for the metabolites selected for residual feed intake (RFI) and feed conversion ratio (FCR)., SMARTER – SMAll RuminanTs breeding for Efficiency and Resilience 772787 European Commission, Peer reviewed, v02