Resultados de investigación

This dataset originates from an experimental study on gonad development in sea bass males at different early maturation stages. Gonads from four individuals (G1-G4) were collected, snap-frozen, and processed for spatial transcriptomics using Visium technology (10X Genomics). Tissue sections were embedded in OCT, cryosectioned, and mounted onto spatial gene expression slides. Transcriptomic analysis involved fixation, staining, cDNA synthesis, and PCR amplification, followed by sequencing on a NovaSeq PE150 platform, yielding 5 Gbp of raw data. This dataset provides high-resolution spatial gene expression data for studying gonadal development and early puberty in sea bass, The research leading to these results has received funding from the Spanish Ministry of Science and Innovation MCIN/AEI/10.13039/501100011033, Grants RYC2019-026426-I, PID2021-122929OB-C31, PID2021-122929OB-C33 and CEX2018-000794-S. AMP also acknowledges a grant PRE2020-094656 funded by MCIN/AEI/10.13039/501100011033 by ESF Investing in your future, With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S)., Peer reviewed

Seagrass meadows are a significant global carbon sink. Most of the carbon sequestered in these ecosystems is found as sedimentary organic carbon, which can vary spatially across seagrass meadows and can be derived from a variety of sources. Here, we investigate intra- and inter-meadow spatial variability in sediment organic carbon storage and quantify potential organic matter sources in three Zostera marina seagrass meadows spanning three estuaries across California (USA). Seagrass sediment organic carbon storage varies as much intra-meadow as it varies across regions. At the intra-meadow scale, we find significant correlations between organic carbon content and mud content (fraction of sediment grains <63 μm, %), C/N ratios, and δ13C values in surface sediments across two meadows. At the regional scale greater organic carbon storage in the presence of seagrass compared to adjacent unvegetated sediments. Additionally, we find that mud content is the best predictor of sediment organic carbon content at the regional scale, indicating an enhanced role for mineral interaction in organic carbon preservation, but not consistently at the localized meadow scale. Approximately one-fourth of the organic carbon preserved in seagrass sediments is derived from seagrass. This research provides insights into the variability of organic carbon storage in seagrass meadows in California at multiple spatial scales. We demonstrate the need to account for small-scale variation of organic carbon storage in seagrass meadows to better estimate the capacity for these ecosystems to serve as effective long-term carbon sinks, Financial support for this work was provided by California Sea Grant to Hill (Award R/HCME-03), This work contributes to the Institut de Ciències del Mar "Severo Ochoa Centre of Excellence" accreditation CEX2024-001494-S funded by AEI 10.13039/501100011033 of the Spanish Ministry of Science and Innovation, Peer reviewed

This repository contains the datasets that underpin the analyses and figures in the ISME Journal article 'Plastic leachates promote protozoan growth' by Jessy Le Du-Carree, Cristina Romera-Castillo, and Rodrigo Almeda, published 2025 (DOI: [DOI or accession link]). The files are: Bacteria_concentrations.xlsx — Bacterial abundance/concentration measurements. CDOM_FDOM.xlsx — Chromophoric and fluorescent dissolved organic matter (CDOM/FDOM), and dissolved organic carbon (DOC) data. Cell_concentration-size_oxyrrhis.xlsx — Oxyrrhis marina cell concentrations and size metrics. EEMs.xlsx — Excitation–Emission Matrix (EEM) fluorescence data. These datasets are shared to ensure transparency and reproducibility and constitute the complete data used in the published manuscript. Please cite the ISME Journal article above when reusing any portion of these data, This study was funded by the Spanish Ministry of Science and Innovation and the National Agency of Research through the MICROPLEACH project (Agencia Estatal de Investigación, PID2020-120479 GA-I00/AEI/10.13039/501100011033) to RA. It was also supported by a “Juan de la Cierva” grant from the Spanish Ministry of Science and Innovation to JLD and a “Ramón y Cajal” grant from the Spanish Ministry of Science (RYC2018-025770-I) to RA. CRC was also supported by a “Ramón y Cajal” grant from the Spanish Ministry of Science (RYC2020-029555-I) and acknowledges the “Severo Ochoa Centre of Excellence” accreditation (CEX2019-000928-S). We sincerely thank Torkel Nielsen (DTU Aqua, Denmark) for providing the Rhodomonas and Oxyrrhis cultures, and Alex Campillo (CSIC, Barcelona, Spain) for his valuable assistance with the bacterial analysis, Peer reviewed

All data sets generated can be found in the Supplementary Material, including the list of primers used for sequencing and the phylogenetic sequence list data sets with corresponding accession numbers, This work was supported by fundings from Spanish MICINN Project DIVINE [PID2023-150672NB-I00]; and Project SMART [PID2020-112978GB-I00], with the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation [CEX2019– 000928- S]. The Japan Science and Technology Agency [JPMJCR24J2]; Japan Society for the Promotion of Science [JSPS KAKENHI 19H05667]; and Japan Society for the Promotion of Science [JSPS KAKENHI 24K18177], Peer reviewed

This work integrates the inspection of high-resolution seismic reflection data to investigate the stratigraphy of the Blanes canyon head. The analysis focuses on the identification of major bounding surfaces, seismic units, and seismic facies to provide new insights into the processes that have controlled its evolution during the Late Quaternary. Specifically, we aim to: i) establish a chronostratigraphic framework based on the correlation of local erosional unconformities with regional surfaces linked to major sea-level fluctuations occurring since the Messinian Salinity Crisis; ii) characterize depositional stacking patterns within the Blanes canyon head sediment infill in order to constrain relative sea-level variability, sediment-routing pathways and the morpho-stratigraphic evolution of the canyon head; iii) determine the influence of the inherited paleorelief and local sedimentary sources on canyon stratigraphic patterns, which exhibit a significant asymmetry between opposing canyon rims; iv) explain the evolution (incision vs infilling) of tributary paleochannels; and v) understand the possible influence of fluvial sediment supply from the nearby Tordera River in the canyon head evolution throughout successive glacio-eustatic cycles., Conclusions: The head of the Blanes Canyon formed on a narrow shelf underlain by a Miocene horst-and-graben basement. The late Quaternary stratigraphic evolution was controlled by tectonic inheritance, glacio-eustatic oscillations (~100 kyr), and laterally variable sediment supply. Four major unconformities (MISs 10, 8, 6, and 2) were identified, recording repeated episodes of erosion and infill. The western rim is depositional and partially fed by the Tordera River, whereas the eastern rim is erosional and sediment-starved. There is no direct fluvial connection with the Tordera River; it mainly contributed to the infill of topographic depressions during sea-level lowstands. Buried tributary paleochannels, aligned with structural lows show incision during lowstands, progradational infill, and subsequent abandonment during the last transgression, indicating that tectonics and marine forcing dominate canyon evolution over fluvial input, - Proyecto ABRIC (RTI2018-096434-B-100) - Proyecto ARCO (TED2021-129426B-I00) - Subvención 2021 SGR 433 de la Generalitat de Catalunya - Beca FPI española (PRE2019-091200) - Acreditación del Centro de Excelencia Severo Ochoa (subvención CEX2024-001494-S financiada por la Agencia Española de Investigación, subvención AEI 10.13039/501100011033)., Peer reviewed

The original raw data from Illumina platform were transformed to Sequenced Reads, known as Raw Data or RAW Reads, by base calling. Raw data are recorded in a FASTQ file, which contains sequencing reads and corresponding sequencing quality. Every read in FASTQ format is stored in four lines, as indicated below: @HWI-ST1276:71:C1162ACXX:1:1101:1208:2458 1:N:0:CGATGT NAAGAACACGTTCGGTCACCTCAGCACACTTGTGAATGTCATGGGATCCAT + #55???BBBBB?BA@DEEFFCFFHHFFCFFHHHHHHHFAE0ECFFD/AEHH Line 1 begins with a '@' character and is followed by the Illumina Sequence Identifiers and an optional description. The details of Illumina sequence identifier are listed in the table below. Identifier Meaning HWI-ST1276 Instrument – unique identifier of the sequencer 71 Run number – Run number on instrument C1162ACXX Flow Cell ID – ID of flow cell 1 Lane Number – positive integer 1101 Tile Number – positive integer 1208 X – x coordinate of the spot. Integer which can be negative 2458 Y – y coordinate of the spot. Integer which can be negative 1 Read number. 1 can be single read or Read 2 of paired-end. N Y if the read is filtered (did not pass), N otherwise. 0 Control number - 0 when none of the control bits are on, otherwise it is an even number CGATGT Illumina index sequences Line 2 is the raw sequence of the read. Line 3 begins with a '+' character and is optionally followed by the same sequence identifiers and descriptions as in Line 1. Line 4 encodes the quality values for the bases in Line 2 and contains the same number of characters as the bases in the read., The objective of this study was to disentangle the genes behind co-localized QTLs for increased yield and stem susceptibility to the maize stem borer, Sesamia nonagrioides Lef. (Mediterranean stem borer, MSB) in the long arm of chromosome 8 of maize. Fine-mapping of QTLs for both traits was performed in a mapping population derived from two near isogenic lines (NILs), NIL16 and NIL95, and RNA-seq has been used to facilitate the identification of QTL candidate genes. RNA-seq analysis was done with RNA extracted from the stem pith of NIL16 and NIL95 collected 30 days after infestation in infested and control plants using four biological replicates for each NIL-treatment combination. Samples were barcoded and prepared for sequencing at Novogene Co., Ltd, where 150 bp paired-end (PE) reads were obtained on an Illumina 1.9., RTI2018-096776-B-C21 and PID2021-122196OB-C21 Projects funded by MCIU/AEI/FEDER, Sequences of 150 bp cDNA paired-end recorded in FASTQ format and contained in files fq.gz. Files (=reads) for each sample are saved in the same folder: Folder S_16_1: Infestation with Sesamia nonagrioides, NIL16, biological replicate 1: S_16_1_MKRN240010851-1A_22C2L2LT4_L4_1.fq.gz S_16_1_MKRN240010851-1A_22C2L2LT4_L4_2.fq.gz S_16_1_MKRN240010851-1A_22CHMWLT4_L8_1.fq.gz S_16_1_MKRN240010851-1A_22CHMWLT4_L8_2.fq.gz Folder S_16_2: Infestation with Sesamia nonagrioides, NIL16, biological replicate 2: S_16_2_MKRN240010852-1A_22F27GLT4_L8_1.fq.gz S_16_2_MKRN240010852-1A_22F27GLT4_L8_2.fq.gz Folder S_16_3: Infestation with Sesamia nonagrioides, NIL16, biological replicate 3: S_16_3_MKRN240010853-1A_22C2L2LT4_L4_1.fq.gz S_16_3_MKRN240010853-1A_22C2L2LT4_L4_2.fq.gz S_16_3_MKRN240010853-1A_22CHMWLT4_L8_1.fq.gz S_16_3_MKRN240010853-1A_22CHMWLT4_L8_2.fq.gz Folder S_16_4: Infestation with Sesamia nonagrioides, NIL16, biological replicate 4: S_16_4_MKRN240010854-1A_22F27GLT4_L8_1.fq.gz S_16_4_MKRN240010854-1A_22F27GLT4_L8_2.fq.gz Folder S_95_1: Infestation with Sesamia nonagrioides, NIL95, biological replicate 1: S_95_1_MKRN240010855-1A_22F27GLT4_L8_1.fq.gz S_95_1_MKRN240010855-1A_22F27GLT4_L8_2.fq.gz Folder S_95_2: Infestation with Sesamia nonagrioides, NIL95, biological replicate 2: S_95_2_MKRN240010856-1A_22F27GLT4_L8_1.fq.gz S_95_2_MKRN240010856-1A_22F27GLT4_L8_2.fq.gz Folder S_95_3: Infestation with Sesamia nonagrioides, NIL95, biological replicate 3: S_95_3_MKRN240010857-1A_22F27GLT4_L8_1.fq.gz S_95_3_MKRN240010857-1A_22F27GLT4_L8_2.fq.gz Folder S_95_5: Infestation with Sesamia nonagrioides, NIL95, biological replicate 4: S_95_5_MKRN240010858-1A_22F27GLT4_L8_1.fq.gz S_95_5_MKRN240010858-1A_22F27GLT4_L8_2.fq.gz Folder C_16_1: Control, NIL16, biological replicate 1: C_16_1_MKRN240010839-1A_22C2L2LT4_L4_1.fq.gz C_16_1_MKRN240010839-1A_22C2L2LT4_L4_2.fq.gz Folder C_16_2: Control, NIL16, biological replicate 2: C_16_2_MKRN240010840-1A_22C2LCLT4_L8_1.fq.gz C_16_2_MKRN240010840-1A_22C2LCLT4_L8_2.fq.gz Folder C_16_3: Control, NIL16, biological replicate 3: C_16_3_MKRN240010841-1A_22C2LCLT4_L8_1.fq.gz C_16_3_MKRN240010841-1A_22C2LCLT4_L8_2.fq.gz Folder C_16_4: Control, NIL16, biological replicate 4: C_16_4_MKRN240010842-1A_22C2LCLT4_L8_1.fq.gz C_16_4_MKRN240010842-1A_22C2LCLT4_L8_2.fq.gz Folder C_95_1: Control, NIL95, biological replicate 1: C_95_1_MKRN240010843-1A_22C2LCLT4_L8_1.fq.gz C_95_1_MKRN240010843-1A_22C2LCLT4_L8_2.fq.gz Folder C_95_2: Control, NIL95, biological replicate 2: C_95_2_MKRN240010844-1A_22F27GLT4_L7_1.fq.gz C_95_2_MKRN240010844-1A_22F27GLT4_L7_2.fq.gz Folder C_95_3: Control, NIL95, biological replicate 3: C_95_3_MKRN240010845-1A_22F27GLT4_L8_1.fq.gz C_95_3_MKRN240010845-1A_22F27GLT4_L8_2.fq.gz Folder C_95_4: Control, NIL95, biological replicate 4: C_95_4_MKRN240010846-1A_22F27GLT4_L8_1.fq.gz C_95_4_MKRN240010846-1A_22F27GLT4_L8_2.fq.gz, No

This database, based on archaeological remains of fish, seabirds and pinnipeds from the Holocene in the Southern Hemisphere, was compiled using a systematic review. The systematic review literature followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Page et al., 2021). The search was performed in English and Spanish in 6th February 2023 in two databases: (a) Scopus and (b) Web of Science, by applying a combination of keywords within the documents’ title, abstract and keywords. Each search string contained four categories connected by the Boolean operator “AND”: study area (countries and provinces), selected species, period and archaeological terms. Each search term was connected by the Boolean operator “OR” within each category. Data from publications meeting all inclusion criteria were used to create a database in Microsoft Excel. The collected data were based on NISP (Number of Identified Specimens) and MNI (Minimum Number of Individuals) from marine fishes, seabirds and pinnipeds associated with archaeological sites (Grayson, 1984; Lyman, 1994). Both are quantitative metrics for analysing faunal assemblages. NISP is the count of identified specimens, allowing for an examination of the diversity and abundance of faunal remains, while MNI refers to the minimum number of individuals per taxonomic category present in the assemblages (Grayson, 1984; Lyman, 1994). We also collected data from the location (latitude and longitude) and radiocarbon dating of each archaeological site. In some cases, coordinates were not provided, but all publications included a map, allowing us to infer the coordinates using Google Earth Pro (version 7.3.6.9345). The Holocene is divided into three periods: the boundary between the Early and Middle Holocene is set around 8,200 years BP, and the Middle-Late Holocene around 4,200 years BP (Walker et al., 2012). Many publications provided multiple radiocarbon dates with their standard deviations; in these cases, we computed an estimated average of the combined dates and the precision of that estimate following Borenstein et al., (2010). Radiocarbon dates were reported either as years BP (Before Present) or years cal. BP (calibrated Before Present). In the context of marine ecosystems in the Southern Hemisphere, radiocarbon dating can be influenced by regional variations in atmospheric ¹⁴C levels and ocean reservoir effects, making calibration essential for accurate chronological reconstructions (Hogg et al., 2020). Calibration involves using region-specific curves. Accordingly, we used SHCal20 (Hogg et al., 2020) with the Calib v8.2 program (Stuiver & Reimer, 1993). This database contains two main parts: the README, where you can find all the data collected in each column along with an explanation of each item and the complete database, This work was supported by MCIN/AEI/10.13039/501100011033 and NextGenerationEU/PRTR, Grant no. FJC2020-043762-I to M.B. This research was also supported by the project ProOceans (PID2020-118097RB-I00). This research contributes to the objectives of Q-MARE (a PAGES working group). Acknowledgement to “Severo Ochoa Center of Excellence” grant CEX2019-000928-S. This research is also part of the Integrated Marine Ecosystem Assessments (iMARES) research group funded by Agència de Gestió d’Ajuts Universitaris i de Recerca (Generalitat de Catalunya) Grant no. 2021 SGR 00435, Peer reviewed

The escalating threat of antimicrobial resistance calls for novel therapeutic agents. This study employed a ligand-based design approach to develop three series of N-arylpyrrole derivatives (Va–e, VIa–e, and VIIa–e), refined through molecular modeling. Synthesized compounds were evaluated against ESKAPE pathogens, MRSA, and Mycobacterium phlei. Series Va–e showed the most promise, with compounds Vb, Vc, and Ve outperforming levofloxacin against MRSA (MIC = 4 μg/mL vs. 8 μg/mL). Vc also exhibited activity against E. coli, K. pneumoniae, and A. baumannii, and showed significant inhibition against M. phlei (MIC = 8 μg/mL). Compounds were evaluated for antibiofilm and antivirulence properties, targeting resistance mechanisms linked to infection persistence and dissemination. Most exhibited broad-spectrum biofilm inhibition and antivirulence activity. Cytotoxicity studies revealed selectivity for bacterial cells. ADMET studies supported drug-like properties. Docking studies suggested UPPP inhibition as the potential mechanism. SAR analysis was conducted to support future optimizations., The researchers did not obtain any funding for the work they submitted. The publishing fee is covered under the CSIC agreement with Taylor & Francis. GY was supported by AYUDAS JUAN DE LA CIERVA-INCORPORACIÓN (IJC2020-044166-I). This work is also supported by the Ministerio de Ciencia, Innovación y Universidades Spain., Peer reviewed

This dataset includes metabolic data and different functional traits of two different pine species including trees in decline and healthy trees. One dataset includes all different shared metabolites identified in the two species and individuals sampled under peak drought stress. The second dataset includes functional traits from gas exchange, hydraulics and osmotic relationships. These functional traits were assessed during two study years with contrasting summer drought., MCIN/AEI /10.13039/501100011033: PID2019-110273RB-I00 MCIN/AEI /10.13039/501100011033: PID2022-142746NB-I00 EU NextGenerationEU/PRTR: TED2021-131947B-100, Peer reviewed

[Data availability] The Argania spinosa genome project is available in the NCBI BioProject database under accession PRJNA294096, and the biological sample used in this study is registered in the BioSample database under accession SAMN04014715. The nuclear genome assembly used for all analyses is available in the NCBI Genome/GenBank database under accession GCA_003260245.2. All annotation data and derived resources are provided through a single Zenodo repository (https://doi.org/10.5281/zenodo.17901083). This archive includes the soft-masked reference assembly, unified genome annotation GFF3, predicted proteome FASTA, repeat and ncRNA annotation files, and transcription factor list. When working with genomic coordinates, users should reference the NCBI genome assembly accession GCA_003260245.2, which defines the scaffold names and coordinate system used in all files. For most downstream analyses, the scaffold-level assembly and unified GFF3 are the recommended starting point, as they provide the most up-to-date and internally consistent view of the genome., [Code availability] No custom code was developed specifically for this study. All analyses were performed using publicly available software tools described in the Methods section, with version numbers and key parameters reported to ensure reproducibility. Users can reproduce or adapt the annotation and validation steps using these tools together with the data hosted in the Zenodo repository (https://doi.org/10.5281/zenodo.17901083)., We present a comprehensive annotation dataset for the scaffold-level nuclear genome assembly of the argan tree (Argania spinosa (L.) Skeels, Sapotaceae). Using Illumina whole-genome shotgun reads that we previously generated for the "Argan Amghar" individual and deposited under BioProject PRJNA294096, together with the corresponding GenBank assembly GCA_003260245.2, we re-assembled and curated a 690 Mbp draft with scaffold N50 of 25 Mbp and L50 of 11 large macro-scaffolds. Ab initio gene prediction with AUGUSTUS and GeneMark-ES, integrated by EVidenceModeler, produced 51,078 protein-coding genes and 2,081 non-coding RNA genes, while repeat annotation covers 53.0% of the assembly. Functional annotation combined eggNOG-mapper, InterProScan and BLASTp searches against UniProtKB/Swiss-Prot to assign curated functions, domains and Gene Ontology terms to 32,785 genes and to support 25,484 proteins with UniProt evidence. BUSCO analyses indicate high completeness of the assembly gene space and completeness of the predicted proteome (74.6%). All primary data products, including a unified GFF3 file and the predicted proteome FASTA, are openly available via NCBI and Zenodo ( https://doi.org/10.5281/zenodo.17901083 )., The computational resources of HPC-MARWAN are provided by the National Center for Scientific and Technical Research (CNRST), Rabat, Morocco, Peer reviewed