Resultados de investigación

Data and code for Eskuche-Keith et al. "Temperature alters the size selectivity of Southern Ocean fish", Nature Communications 2024, Peer reviewed

Supporting information features molecular structure and magnetic properties of Dy2, as well as susceptibility tensor and calculated charges and potentials of Dy1., Peer reviewed

Supplementary material containing additional synthesis protocols, spectroscopic characterization and additional microscopy images is included free of charge., Peer reviewed

SUPPLEMENTARY FIGURE S1 | NIH Roadmap data highlighting chromatin states surrounding MYEOV. (A) H3K4me1 (orange), H3K27ac (blue) and H3K4me3 (green) ChIP-seq data taken from NIH Roadmap data for GM12878, B cells, lung, liver and pancreatic tissues alongside DNase-seq data for GM12878 and B cells. Data was visualised on WashU genome browser. MYEOV-3’-putative enhancer is highlighted with an orange block. (B) Presence of H3K27ac peaks at MYEOV’s 3’ UTR region across 169 primary cell samples, tissues and cell lines. NarrowPeak ChIP-seq H3K27ac files were obtained from ENCODE and presence of peaks in chr11:69,297,041-69,298,854 was determined for each tissue. Data shown corresponds to Supplementary Table S2. Word clouds show biosample terms specific to groups with and without peaks, with darker coloured and larger words representing biosamples with more replicates. SUPPLEMENTARY FIGURE S2 | Interaction observed when CCND1 is taken as viewpoint. Promoter capture Hi-C data across five different tissues/cell lines taken from Jung et al.; these being GM12878/GM19240 lymphoblastoid cell line, lung, liver and pancreatic tissues and H1-derived mesenchymal stem cells. CCND1 was taken as bait and interactions were filtered to only show significant interactions over −log10(P-value) = 2 and normalised counts. Data was visualised on 3DIV. SUPPLEMENTARY FIGURE S3 | Interaction observed when MYEOV is taken as the viewpoint. Promoter capture Hi-C data across five different tissues/cell lines taken from Jung et al.; these being GM12878/GM19240 lymphoblastoid cell line, lung, liver,pancreatic tissues and H1-derived mesenchymal stem cells. MYEOV was taken as bait and interactions were filtered to only show significant interactions over −log10(P-value) = 2 and normalised counts. Data was visualised on 3DIV. SUPPLEMENTARY FIGURE S4 | Interaction observed when LTO1/ORAOV1 is taken as bait. Promoter capture Hi-C data across five different tissues/cell lines taken from Jung et al.; these being GM12878/GM19240 lymphoblastoid cell line, lung, liver and pancreatic tissues and H1-derived mesenchymal stem cells. ORAOV1 (LTO1) was taken as bait and interactions were filtered to show only significant interactions over −log10(P-value) = 2 and normalised counts. Data was visualised on 3DIV. SUPPLEMENTARY FIGURE S5 | BLAST Hit for MYEOV locus seen in seven primate species. Ensembl BLAST search was performed using the MYEOV locus as a query against seven primate species which included chimpanzee (Pan troglodytes), gorilla (Gorilla gorilla), orangutan (Pongo abelii), gibbon (Nomascus leucogenys), rhesus Macaque (Macaca mulatta), marmoset (Callithrix jacchus), and squirrel monkey (Saimiri boliviensis). Conserved sequences are shown as red rectangles with the percentage ID of BLAST hit determined by the shade. Chromatin data also shown from B cells with H3K4me1 (orange), H3K4me3 (green) and H3K27ac (blue) ChIP-seq data highlighted. MYEOV-3’-putative enhancer shaded in blue. Data was visualised on the Ensembl. SUPPLEMENTARY FIGURE S6 | Conservation of gene synteny surrounding BLAST sequence. Region which surrounds Ensembl BLAST top hit was located across five different species, these being human, dogs, cows, goats and chickens when MYEOV 3’UTR was used as the query sequence. Each BLAST hit is denoted with a red line. Data was visualised on the Ensembl. SUPPLEMENTARY FIGURE S7 | Conservation of H3K27ac signal across mammalian tissue. H3K27ac (blue) and H3K4me3 (orange) ChIP-seq data taken from liver tissue of six species including humans, mice, rats, dogs, cows and pigs (Villar et al. 2015). Also, H3K4me1 and H3K4me3 ChIP-seq data from mouse liver tissue (Shen et al. 2012). Conserved region highlighted in red is the homologous sequence determined from multiple sequence alignment. In each species, we indicate if the BLAST hit corresponded to the positive or negative strand of the species reference genome. Data was visualised on IGV. SUPPLEMENTARY FIGURE S8 | Comparing histone data from Roller et al. to Villar et al. ChIP-seq data for three mammalian species was taken from both Roller et al and Villar et al. This included H3K27ac (blue), H3K4me1 (orange) and H3K4me3 (green) for rats, dogs and pigs liver tissue. Conserved region highlighted in red is the homologous sequence determined from multiple sequence alignment. Data was visualised on IGV. SUPPLEMENTARY FIGURE S9 | Conservation of enhancer chromatin state across multiple mouse tissues. Top Panel: Highlights ChIP-seq for H3K4me1 (orange), H3K4me3 (green) and H3K27ac (blue) in CH12 mouse lymphoma cell line, lung, liver and bone marrow tissue in mice. Alongside, ChIP-seq data for CTCF in CH12 mouse lymphoma cell line. Bottom Panel: Show zoom in region surrounding conserved region which is highlighted in yellow and is the homologous sequence determined from multiple sequence alignment. SUPPLEMENTARY TABLE S1 | This table presents sources used for studying chromatin states and regulatory regions across different species and tissues. It contains sources of chromatin profiling data, including ChIP-seq and ATAC-seq, for multiple species and tissues. The data include information on histone marks (H3K4me1, H3K4me3, H3K27ac, H3K27me3, H3K36me3) and are sourced from diverse studies involving primates, other mammalian species, and chicken. SUPPLEMENTARY TABLE S2 | This table presents the results of an extensive analysis of the presence or absence of H3K27ac peaks within MYEOV’s 3'UTR region in a wide range of human tissues, cell lines, and cell types, shedding light on the tissues where this enhancer is active. SUPPLEMENTARY TABLE S3 | This table presents the data resources used to investigate the regulatory roles of MYEOV’s enhancer element in both human and mouse genomes and identification of gene targets of MYEOV’s enhancer. The table includes sources of RNAseq, ChIP-seq data for histone modifications (H3K4me1, H3K4me3, H3K27ac) and CTCF in multiple mouse tissues, including CH12 mouse B cell lymphoma cell line, adult liver cells, lung liver cells, and bone marrow. Additionally, it provides sources of human PCHi-C studies in specific tissues associated with cancer. The table also contains data on long-range chromatin interactions, ChIA-PET data, and CTCF data to explore potential mechanisms of enhancer-target promoter interactions and confirm topologically associated domain (TAD) structures. SUPPLEMENTARY TABLE S4 | This table presents DNA sequence conserved regions of MYEOV’s enhancer element across a diverse set of 17 species, pinpointed by BLASTN search, and multiple sequence alignments, are documented in this table. SUPPLEMENTARY TABLE S5 | This table presents a summary of the interactions observed by PCHi-Cdata between MYEOV, LTO1 and CCND1 highlighting the primary cell types, tissues and cell lines where the interactions were identified. Abbreviation. put. putative., Peer reviewed

Peer reviewed

The objective of this study was to identify as many as possible the proteins expressed in the promastigote stage of Leishmania donovani (HU3 strain). For this purpose, after processing the protein extracts (see next section), the resulting peptides were analysed by reverse phase-liquid chromatography (RP-LC)-MS/MS (Dynamic Exclusion Mode). Mass spectra were searched by PEAKS Studio XPro search engine (Bioinformatics Solutions Inc., Waterloo, Ontario, Canada)., Peer reviewed

This dataset is associated with the manuscript entitled "Field Assessment of Biochar Interactions with Chemical and Biological N Fertilization in Pointed White Cabbage"., We gratefully acknowledge the financial support of the project PID2021-12886OB100 funded by MCIN/AEI /10.13039/501100011033/ and ERDF A way of making Europe. R. Castejón-del Pino was supported by the grant PRE2019-088308 funded by MICIU/ AEI /10.13039/501100011033 and ESF Investing in your future within the project RTI2018-099417-BI00., Peer reviewed

Document S1. Methods S1 and supplemental references.--Table S1. Summary of the datasets of combinatorial community composition and function analyzed in this study, related to Figure 2..--Table S2. 16S rRNA gene sequences of the environmental isolates used in our experiment, related to Figure 1., Peer reviewed

[Description of methods used for collection/generation of data] Data were acquired through an RGB camera mounted on a UAV at an altitude of 11m., Identification of weed species at the early stages of growth is critical for precision agriculture. Accurate detection and classification to species level allows targeted control measures to be taken, significantly reducing pesticide use. This dataset consists of RGB images, captured with a Sony ILCE-6300L camera mounted on an unmanned aerial vehicle (UAV) at 11 meters altitude. The dataset covers several agricultural fields in Spain, focusing on two summer crops: corn and tomato. It is designed to improve the accuracy of early season weed detection by including images from two phenological stages. Specifically, the dataset contains 31,002 labeled images from the early growth stage - maize with four leaves unfolded (BBCH14) and tomato with the first flower bud visible (BBCH501) - as well as 36,556 images from a later growth stage - maize with seven leaves unfolded (BBCH17) and tomato with the ninth flower bud visible (BBCH509). In maize, weed species include Atriplex patula, Chenopodium album, Convolvulus arvensis, Datura ferox, Lolium rigidum, Salsola kali and Sorghum halepense. In tomato, weed species include Cyperus rotundus, Portulaca oleracea and Solanum nigrum. The images, stored in JPG format, were labeled by partitioning orthomosaics, with each image corresponding to a specific plant species. This dataset is ideal for developing advanced deep learning models, such as CNN and ViT, for early detection and classification of weed species in corn and tomato crops using UAV imagery. By providing this dataset, we aim to advance UAV-based weed detection and mapping technologies, contributing to precision agriculture with more efficient and accurate tools that promote sustainable and profitable agricultural practices., This work was supported by the Spanish Research State Agency (AEI) through the Project PID2020-113229RB-C41/AEI/10.13039/501100011033. The lead author, G.A. Mesías-Ruiz has been a beneficiary of a FPI fellowship by the Spanish Ministry of Education and Professional Training (PRE2018-083227)., Peer reviewed

Details on the structural (Table S1), EELS (Figures S1−S2), densities of states (Figure S3) and BSE data (Tables S2−S5) are provided. Table S6 summarizes the main results in terms of optical and excitonic properties of SM-, ZT-BiVO4, Anatase & Rutile TiO2., Peer reviewed