BUSCADOR RECOLECTA

Table_1_Rare earth elements distribution in the Gulf of Cádiz (SW Spain): geogenic vs. anthropogenic influence.docx, There is a current interest in the study of the geochemical behavior of the rare earth elements (REE) in aquatic systems since their identification as potential microcontaminants in natural waters. In this context, here we report the concentrations and patterns of dissolved REE (dREE) in the waters of the Gulf of Cádiz (GoC) and its major estuaries (Guadiana, Tinto-Odiel and Guadalquivir). Contamination in this area by metals has been extensively reported, linked to acid-mine inputs resulting from the mineralization of the Iberian Pyrite Belt, discharged mainly to the Tinto-Odiel river. However, the impact of these inputs on the concentrations and distribution of the dREE in the coastal waters of the GoC has not been addressed yet. Accordingly, elevated concentrations of dREE were obtained in the Tinto-Odiel estuary compared to the Guadiana and Guadalquivir, reflecting the impact of acid-mine drainage on this system. Only a significant fraction of anthropogenic gadolium (Gd) was observed in the Guadalquivir estuary, as a result of the input from major urban areas, where anthropogenic Gd fractions higher than 70% over the total dissolved pool were obtained for the freshwater end-member. Regarding the surface waters of the GoC, typical NE Atlantic distribution patterns of dREEs were obtained, but modified by two different end-members within this region. Accordingly, and despite the low water discharge of the Tinto-Odiel river, its elevated concentrations lead to an increase in the concentrations of dREEs in the nearshore waters of the GoC and producing a distinctive signature as observed for the MREE anomalies and HREE/LREE ratios. At the easternmost stations, close to the Strait of Gibraltar, these signals are also impacted by the inflow of Mediterranean waters and also by the discharge of the Guadalquivir river., Peer reviewed

The files contain the numerical data of the figures of the article "Footprints of atomic-scale features in plasmonic nanoparticles as revealed by Electron Energy Loss Spectroscopy" published in Physical Chemistry Chemical Physics (doi.org/10.1039/D4CP01034E) and written by Mattin Urbieta, Marc Barbry, Peter Koval, Alberto Rivacoba, Daniel Sánchez-Portal, Javier Aizpurua, and Nerea Zabala. The data files are organized in different folders and subfolders corresponding to each of the figures in the paper., Project No. PID2022-139579NB-I00 funded by MCIN/AEI/10.13039/501100011033 and ”ERDF A way of making Europe”; Basque Department of Education (Grant No. IT1526-22 and IT1569-22 and PhD Grant); Grants PID2019-107338RB-C66 and PID2022-140845OB-C66 funded by MCIN/AEI/10.13039/501100011033; Basque Department of Education; Departamento de Educación of the Basque Government through a PhD grant; Fellows Gipuzkoa program of the Gipuzkoako Foru Aldundia through the FEDER funding scheme of the European Union, “Una manera de hacer Europa”; DIPC, Euskampus and CFM;, Peer reviewed

Files: trait_data.csv – a comma-delimited file with population-specific annual fitness-related trait data. Traits included: laying date (LD, laying date of the first egg, where 1 = April 1st), clutch size (CS, number of eggs) and fledgling number (FN, number of nestlings 13-16 days after hatching). Annual values for these traits were based on data from individual broods that were not subjected to experimental manipulations (e.g. clutch size manipulation or cross-fostering). Fledgling numbers were based on broods with at least one fledgling.-- location_data.csv – a comma-delimited file with latitude and longitude (in decimal degrees) for all 44 locations.-- climate_data.csv – a comma-delimited file with location-specific annual climate data. Climate variables included: North Atlantic Oscillation (NAO) index, mean temperature (in degrees Celsius) and mean precipitation (in mm). For each climate variable, we give the average over daily values in February-May.-- data_information.csv – a comma-delimited file with a supplementary table on data owners and geographical information per location, study length per population, and sample sizes per trait, species, and location.-- analysis.R - an R file with code to run analyses of temporal variation in trait values, effects of climate variables on trait values, and spatial synchrony in trait values.-- Climate data sources: Daily NAO-indices were extracted from the Climate Prediction Center of the National Weather Service (https://www.cpc.ncep.noaa.gov).-- Daily mean temperature and mean precipitation were extracted from the E-OBS gridded dataset version 20.0e (Cornes et al. 2018, DOI: 10.1029/2017JD028200).-- Daily mean precipitation for Vlieland (Loc: VLI) was extracted from a Royal Dutch Meteorological Institute (KNMI) weather station (Oost-Vlieland; https://www.knmi.nl/nederland-nu/klimatologie/monv/reeksen).-- See README.docx for more detail., Annual trait data, location information, and climate data from 86 populations of blue tit (Cyanistes caeruleus, n = 31), great tit (Parus major, n = 35) and pied flycatcher (Ficedula hypoleuca, n = 20) across Europe. R code for the analyses of temporal variation in trait values, effects of climate variables on trait values, and spatial synchrony in trait values., Centre for Biodiversity Dynamics (CBD): The Research Council of Norway, Multidimensional pen: quantitative genetics and phylogenetics comparative plumage of birds: National Science Center, The effect of steroid hormones on the parameters of genetic variation in wild bird populations: National Science Center, JCS was funded by project CGL-2020 PID2020-114907GB-C21., DC was supported by the Hungarian Academy of Sciences (MTA Premium Postdoctoral Research Program; ID: 2019-353)., JM-P was funded by ARAID and the Spanish Ministry of Education and Science (PID2019-104835GB-I00)., The Pirio and Rouvière field work was funded by the OSU-OREME., The Zvenigorod field work was supported by RSF-FWO (#20-44-01005)., MDB was supported by Natural England., ME and RP were funded by University of Antwerp and FWO Flanders., The Norwegian data is collected as part of a Terrestrial monitoring program financed by the Norwegian Environment Agency and the Ministry of Climate and Environment., BK was funded by the Max Planck Society., The Gotland field work was supported by the Swedish Research Council, the CNRS, and the Polish National Science Centre (UMO-2015/18/E/NZ8/00505, UMO-2012/07/D/NZ8/01317)., EB was funded by the Ministry of Science and Innovation (project PID2021-122171NB-I00)., SMD was funded by the DECRA fellowship (DE180100202)., Peer reviewed

The file contains: Supplementary Information 1: Table 1. Data Description and Sources.-- Supplementary Information 2: Table 2. Results of invariance analysis of the model presented in the results section of the manuscript.-- Supplementary Information 3: Fig. 1. Data Distribution and Student’s t-Test by Protection Status.-- Supplementary Information 4: Fig. 2. Correlation Plots.-- Supplementary Information 5: Fig. 3.-- Supplementary Information 6: Fig. 4.-- Supplementary Information 7: Fig. 5. Results of SEM showing the linkages with land-use intensity for plots belonging to protected grasslands from all three regions.-- Supplementary Information 8: Fig. 6. Results of SEM showing the linkages with fertilising intensity as the land-use variable for a. protected plots and b. non-protected plots.-- Supplementary Information 9: Fig. 7. Results of SEM showing the linkages with mowing intensity as the land-use variable for a. protected plots and b. non-protected plots.-- Supplementary Information 10: Fig. 8. Results of SEM showing the linkages with grazing intensity as the land-use variable for a. protected plots and b. non-protected plots.-- Supplementary Information 11: List of most common species found in the studied plots (by abundance)., Peer reviewed

Explanation note: table S1. Definitions of the response variables used to classify impact types on native species (i.e. individuals of the same taxon) and communities (i.e. individuals of several species at a site). table S2. Publication level information in PLANTIMPACTSEUROPE_publicationLevel. xlsx. The PLANTIMPACTSEUROPE database can be accessed at https://figshare.com/s/0a890d22bf5632fe5cb5. table S3. Invasive plant information and field studies testing for impacts in PLANTIMPACTSEUROPE_impactsDatabase. xlsx. The PLANTIMPACTSEUROPE database can be accessed at https://figshare.com/s/0a890d22bf5632fe5cb5. Storage location and medium: The PLANTIMPACTSEUROPE database can be accessed at https://figshare.com/s/0a890d22bf5632fe5cb5. (1) PLANTIMPACTSEUROPE_publicationLevel. xlsx: 266 publications with indication of countries, habitats and study locations, 312 entries (rows excluding the header), 8 columns, 59 KB. (2) PLANTIMPACTSEUROPE_impactsDatabase. xlsx: 4259 impacts (rows excluding the header), 16 columns, 348 KB., This dataset is made available under the Open Database License (http://opendatacommons.org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited., Peer reviewed

(A) Above: Sequence motif enriched in C. elegans HE cluster HMT promoters, relative to other HMTs promoters. Below: previously reported EFL-2 binding motif. (B) Binding of the C. elegans Retinoblastoma orthologue LIN-35 upstream of the TSS of the HE cluster, other HMT genes, and random genes; p-values from Wilcoxon test. (C) Enrichment for transcription factor binding, from ENCODE ChIP-seq experiments, upstream of human HMT genes. Odds ratios and p-value derived from Fisher’s exact test. (D) Boxplots show median total HMT or NNMT expression percentile drawn from 1,000 iterations of pan-cancer sampling of tumours with wild-type RB1 or potentially deleterious RB1 mutations; p-value derived from t test. (E) Total HMT expression in small cell lung cancer cell lines from the CCLE with wild-type RB1 or deleterious RB1 mutations; p-value derived from t test. (F) Estimated E2F1 activity vs. total HMT expression (both corrected for confounders) in breast cancer primary tumours from the TCGA. (G) Potential architectures of the GRN linking RB1, NNMT, and HMTs. (H) Linear model t-values explaining total HMT and NNMT expression for RB1 mutation status as the sole explanatory variable or jointly considered with NNMT/HMT expression respectively; p-value derived from t test. Underlying data for all panels can be found in https://zenodo.org/record/8383542. CCLE, Cancer Cell Line Encyclopedia; GRN, gene regulatory network; HMT, histone methyltransferase; NNMT, nicotinamide N-methyltransferase; Rb, Retinoblastoma; TCGA, The Cancer Genome Atlas; TSS, transcription start site., Peer reviewed

(A) Boxplot shows t-values from linear mixed effects model for sample PEMT expression predicting ChIP-seq signal for various histone marks (label left) on gene bodies, promoters or repetitive elements (subpanel headers) in patient tissue samples collected as part of the ENCODE project. The number of individual sites is noted on the plot for each boxplot; p-values derive from paired Wilcoxon tests against a null distribution calculated by the mean t-value at each locus for 1,000 random expressed genes. (B) Heatmap showing H3K4me3 ChIP-seq signal (log2 fold change over input) over 1,000 random genes for 4 samples from the squamous epithelium of the esophagus arranged in order of PEMT expression. (C) Boxplot shows t-values from generalised linear models for NNMT expression (RNA-seq) predicting ChIP-seq signal for various histone marks (label left) on gene bodies and promoters in cell lines of the NCI60 cancer cell line panel. The number of individual sites is noted on the plot for each boxplot; p-values derive from paired Wilcoxon tests against a null distribution calculated by the mean t-value at each locus for 1,000 random expressed genes. (D) Boxplot shows t-values from generalised linear models for NNMT expression (RNA-seq) predicting ChIP-seq signal for various histone marks (label left) on different classes of repetitive elements in cell lines of the NCI60 cancer cell line panel. The number of individual sites is noted on the plot for each boxplot; p-values derive from paired Wilcoxon tests against a null distribution calculated by the mean t-value at each locus for 1,000 random expressed genes. Sites shown are from bin with highest ChIP signal (cf. S9D Fig). Underlying data for all panels can be found in https://zenodo.org/record/8383542. HERVs, human endogenous retroviruses; LINEs, long interspersed nuclear elements; LTRs, long terminal repeats; NNMT, nicotinamide N-methyltransferase; SINEs, short interspersed nuclear elements., Peer reviewed

(A) Analysis showing rank percentile position of total HMTs among correlations of NNMT expression to 56,200 genes and vice versa in 48 distinct healthy tissue types from the GTEx project. Bubble size is inversely proportional to the log of the “relative reciprocal score,” the sum of squares of the ranks of total HMTs/NNMT in the reciprocal distribution (see Methods). The dashed grey box indicates correlations in the strongest 2.5% of anticorrelated genes, with tissues labelled. (B) Volcano plot showing Spearman’s correlation and FDR for expression of NNMT vs. 56,200 genes in a pan-cancer analysis of GTEx primary tumours across 48 tissue types. HMT-encoding genes are shown as points coloured according to association with transcriptional regulation; correlation for total HMT expression is shown as a black point. (C) Analysis showing rank percentile position of total HMTs among correlations of PEMT expression and vice versa in healthy tissue types from the GTEx project. Bubble size and dashed grey box as in panel 2A. (D) Volcano plot showing Spearman’s correlation and FDR for expression of PEMT vs. 56,200 genes in a cross-tissue analysis of 18 tissue types with a strong HMT-PEMT relationship (within the grey box in panel 2C). HMT-encoding genes are shown as points as in panel 2B. (E) Violin plot showing Spearman’s correlation to PEMT of HMTs (black, right) or other genes (left, grey) in 375 patient samples from the gastroesophageal junction. HMT-encoding genes are shown as points as in panel 2B. (F) Spearman’s correlation vs. PEMT expression of total expression of pooled HMTs added to the pool in a random order in a cross-tissue analysis of tissues with a strong HMT-PEMT relationship (within the grey box in panel 2C); 1,000 individual iterations are shown as black lines, with Loess fit trendline in red. (G) Analysis showing rank percentile position of total HMTs among correlations of PEMT expression to 60,489 genes and vice versa in 33 cancer types from the TCGA. Bubble size and dashed grey box as in panel 2A. (H) PEMT sequentially methylates phosphoethanolamine to produce PC, converting 3 molecules of SAM to SAH. (I) Analysis showing rank percentile position of HMTs classified by their substrate histone lysine residues among correlations of NNMT expression and vice versa in cancer types from the TCGA. Bubble size and dashed grey box as in panel 2A. (J) Analysis showing rank percentile position of HMT sets methylating distinct histone lysine residues among correlations of PEMT expression to 56,200 genes and vice versa in a pan-tissue analysis of 18 tissue types from the GTEx with a strong HMT-PEMT relationship (within the grey box in panel 2C). Bubble size and dashed grey box as in panel 2A. (K) Analysis showing rank percentile position of HMT sets methylating distinct histone lysine residues among correlations of PEMT expression and vice versa in a pan-cancer analysis of 7 cancer types from the TCGA with a strong HMT-PEMT relationship (within the grey box in panel 2G). Bubble size and dashed grey box as in panel 2J. (L) Violin plot showing healthy tissue sample PI, a measure of proliferation inferred from sample RNA-seq gene expression data, for 48 tissue types of the GTEx arranged by the strength of the anticorrelating relationship between PEMT and total HMTs. Note the x axis is inverted as a lower relative reciprocal score indicates a stronger relationship. (M) Violin plot showing tumour PI for 31 cancer types of the TCGA arranged by the strength of the anticorrelating relationship between NNMT and total HMTs. Underlying data for all panels can be found in https://zenodo.org/record/8383542. FDR, false discovery rate; GTEx, Genotype-Tissue Expression; HMT, histone methyltransferase; NNMT, nicotinamide N-methyltransferase; PC, phosphatidylcholine; PI, proliferative index; SAH, S-adenosyl homocysteine; SAM, S-adenosyl methionine; TCGA, The Cancer Genome Atlas., Peer reviewed

(A) Volcano plot showing Pearson’s correlation and FDR for 225 metabolites to total HMT expression (total RNA-seq median of ratios-normalised pseudocounts) across 927 cancer cell lines from the CCLE. (B) Volcano plot showing Pearson’s correlation and FDR for expression of 10,275 expressed genes to levels of 1MNA across 927 CCLE cancer cell lines. The top and bottom 2.5% of points are shown in darker grey. HMT-encoding genes are shown as points coloured according to their association with transcriptional activation (green), repression (magenta), or an unclear relationship (blue). Pearson’s r for total HMT expression is shown as a black point. (C) PCA of metabolite levels across 927 cancer cell lines from the CCLE. 1MNA is highlighted with a red circle. (D) NNMT and HMTs both convert SAM to SAH and so can affect cellular methylation potential by acting as a “sink.” (E) Volcano plot showing Spearman’s correlation and FDR for expression of NNMT vs. 52,440 genes in a pan-cancer analysis of 927 CCLE cell lines across 23 cancer types. HMT-encoding genes are shown as points as in panel 1B. (F) Volcano plot showing Spearman’s correlation and FDR for expression of NNMT vs. 60,489 genes in a pan-cancer analysis of TCGA primary tumours across 33 cancer types. HMT-encoding genes are shown as points as in panel 1B. (G) Violin plot showing Spearman’s correlation to NNMT for HMTs (black, right) or other genes (left, grey) in 79 primary ACC tumours from the TCGA. Individual HMT-encoding genes are shown as points as in panel 1B. (H) Spearman’s correlation vs. NNMT expression of total expression of pooled HMTs added to the pool in a random order, and 1,000 individual iterations are shown as black lines, with the locally estimated smoothing (Loess fit) trendline shown in red. (I) TCGA pan-cancer analysis showing rank percentile position of total HMTs among correlations of NNMT expression to 60,489 genes and vice versa in 33 distinct cancer types. Bubble size is inversely proportional to the log of the “relative reciprocal score,” the sum of squares of the ranks of total HMTs/NNMT in the reciprocal distribution. The dashed grey box indicates correlations in the strongest 2.5% of anticorrelated genes. Underlying data for all panels can be found in https://zenodo.org/record/8383542. 1MNA, 1-methylnicotinamide; ACC, adrenocortical carcinoma; CCLE, Cancer Cell Line Encyclopedia; FDR, false discovery rate; HMT, histone methyltransferase; NNMT, nicotinamide N-methyltransferase; SAH, S-adenosyl homocysteine; SAM, S-adenosyl methionine; TCGA, The Cancer Genome Atlas., Peer reviewed

Individual HMT levels in Rb-mutant tumours in TCGA., Peer reviewed