cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.26992138
title: Additional file 2 of Analysis of five near-complete genome assemblies of the tomato pathogen Cladosporium fulvum uncovers additional accessory chromosomes and structural variations induced by transposable elements effecting the loss of avirulence genes

description: Additional file 2: Table S1. Cladosporium fulvum isolates for which near-complete genome assemblies were obtained using PacBio HiFi sequencing technology. Table S2. Comparison of the assembled chromosomes of five Cladosporium fulvum isolates. Table S3. Summary of estimated abundance of transposable elements in the genomes of five Cladosporium fulvum isolates. Table S4. Summary of regions of the five Cladosporium fulvum genomes affected by Repeat-Induced Point (RIP) mutations. Table S5. Update of the gene annotations of Cladosporium fulvum isolate Race 5. Table S6. Summary of genes from different functional categories and select sub-categories in five Cladosporium fulvum genomes. Table S7. Genes encoding carbohydrate-active enzymes (CAZymes) in five Cladosporium fulvum genomes. Table S8. Genes encoding proteases in five Cladosporium fulvum genomes. Table S9. Genes encoding cytochromes P450 in five Cladosporium fulvum genomes. Table S10. Genes encoding ABC and MFS transporters in five Cladosporium fulvum genomes. Table S11. Genes encoding key secondary metabolite enzymes in five Cladosporium fulvum genomes. Table S12. Genes encoding secreted proteins in Cladosporium fulvum genomes. Table S13. Genes encoding candidate effector proteins in five Cladosporium fulvum genomes. Table S14. Number of genes in five Cladosporium fulvum genomes assigned to different Gene Ontology (GO) terms and EuKaryotic Ortholog Group (KOG) categories. Table S15. Accessory genes from five Cladosporium fulvum genomes. Table S16. Summary of pairwise synteny blocks in pairwise alignments of five Cladosporium fulvum genomes. Table S17. Number and type of structural variations (SVs) identified in four Cladosporium fulvum genomes. Table S18. Structural variations (INDELs) affecting genes in the genome of Cladosporium fulvum. Table S19. Homologs and expression of predicted genes from the dispensable chromosomes Chr14 and Chr15 of Cladosporium fulvum.
DOI: 10.6084/m9.figshare.26992138.v1
title: Additional file 2 of Analysis of five near-complete genome assemblies of the tomato pathogen Cladosporium fulvum uncovers additional accessory chromosomes and structural variations induced by transposable elements effecting the loss of avirulence genes

description: Additional file 2: Table S1. Cladosporium fulvum isolates for which near-complete genome assemblies were obtained using PacBio HiFi sequencing technology. Table S2. Comparison of the assembled chromosomes of five Cladosporium fulvum isolates. Table S3. Summary of estimated abundance of transposable elements in the genomes of five Cladosporium fulvum isolates. Table S4. Summary of regions of the five Cladosporium fulvum genomes affected by Repeat-Induced Point (RIP) mutations. Table S5. Update of the gene annotations of Cladosporium fulvum isolate Race 5. Table S6. Summary of genes from different functional categories and select sub-categories in five Cladosporium fulvum genomes. Table S7. Genes encoding carbohydrate-active enzymes (CAZymes) in five Cladosporium fulvum genomes. Table S8. Genes encoding proteases in five Cladosporium fulvum genomes. Table S9. Genes encoding cytochromes P450 in five Cladosporium fulvum genomes. Table S10. Genes encoding ABC and MFS transporters in five Cladosporium fulvum genomes. Table S11. Genes encoding key secondary metabolite enzymes in five Cladosporium fulvum genomes. Table S12. Genes encoding secreted proteins in Cladosporium fulvum genomes. Table S13. Genes encoding candidate effector proteins in five Cladosporium fulvum genomes. Table S14. Number of genes in five Cladosporium fulvum genomes assigned to different Gene Ontology (GO) terms and EuKaryotic Ortholog Group (KOG) categories. Table S15. Accessory genes from five Cladosporium fulvum genomes. Table S16. Summary of pairwise synteny blocks in pairwise alignments of five Cladosporium fulvum genomes. Table S17. Number and type of structural variations (SVs) identified in four Cladosporium fulvum genomes. Table S18. Structural variations (INDELs) affecting genes in the genome of Cladosporium fulvum. Table S19. Homologs and expression of predicted genes from the dispensable chromosomes Chr14 and Chr15 of Cladosporium fulvum.
DOI: 10.6084/m9.figshare.26992153
title: Additional file 1 of A genomics perspective of personalized prevention and management of obesity

description: Additional file 1. Table S1: Published studies supporting the interplay between macronutrient intake, lifestyle and genetic background analyzed in this review article. Table S2: Actionable Gene List for Obesity Management (AnGeL) derived from 313 SNPs associated with macronutrient interactions in obesity management. Table S3: Enrichment results of AnGeL for REACTOME, WIKI and KEGG pathways related to Fig.1A, and for drugs predicted to be associated with the AnGeL gene set related to Fig. 1B.
DOI: 10.6084/m9.figshare.26992153.v1
title: Additional file 1 of A genomics perspective of personalized prevention and management of obesity

description: Additional file 1. Table S1: Published studies supporting the interplay between macronutrient intake, lifestyle and genetic background analyzed in this review article. Table S2: Actionable Gene List for Obesity Management (AnGeL) derived from 313 SNPs associated with macronutrient interactions in obesity management. Table S3: Enrichment results of AnGeL for REACTOME, WIKI and KEGG pathways related to Fig.1A, and for drugs predicted to be associated with the AnGeL gene set related to Fig. 1B.
DOI: 10.6084/m9.figshare.26992165
title: Additional file 1 of Children’s active school transportation: an international scoping review of psychosocial factors

description: Additional file 1. Final version of data chartingR4.
DOI: 10.6084/m9.figshare.26992165.v1
title: Additional file 1 of Children’s active school transportation: an international scoping review of psychosocial factors

description: Additional file 1. Final version of data chartingR4.
DOI: 10.6084/m9.figshare.26992168
title: Additional file 2 of Children’s active school transportation: an international scoping review of psychosocial factors

description: Additional file 2. Characteristics of each sourceR4.
DOI: 10.6084/m9.figshare.26992168.v1
title: Additional file 2 of Children’s active school transportation: an international scoping review of psychosocial factors

description: Additional file 2. Characteristics of each sourceR4.
DOI: 10.6084/m9.figshare.26992171
title: Additional file 3 of Children’s active school transportation: an international scoping review of psychosocial factors

description: Additional file 3. Results of each source of evidenceR4.
DOI: 10.6084/m9.figshare.26992171.v1
title: Additional file 3 of Children’s active school transportation: an international scoping review of psychosocial factors

description: Additional file 3. Results of each source of evidenceR4.
DOI: 10.6084/m9.figshare.26992186
title: Additional file 1 of Decoding leukemia at the single-cell level: clonal architecture, classification, microenvironment, and drug resistance

description: Supplementary Material 1: Supplementary Table S1. The list of abbreviations
DOI: 10.6084/m9.figshare.26992186.v1
title: Additional file 1 of Decoding leukemia at the single-cell level: clonal architecture, classification, microenvironment, and drug resistance

description: Supplementary Material 1: Supplementary Table S1. The list of abbreviations
DOI: 10.6084/m9.figshare.26992198
title: Additional file 3 of Subtropical coastal microbiome variations due to massive river runoff after a cyclonic event

description: Additional file 3. Dataset including all environmental parameters generated and analyzed in this study.
DOI: 10.6084/m9.figshare.26992198.v1
title: Additional file 3 of Subtropical coastal microbiome variations due to massive river runoff after a cyclonic event

description: Additional file 3. Dataset including all environmental parameters generated and analyzed in this study.
DOI: 10.6084/m9.figshare.26992216
title: Additional file 2 of BORIS/CTCFL epigenetically reprograms clustered CTCF binding sites into alternative transcriptional start sites

description: Additional file 2: Supplementary Table S1. A list of TSSs identified through CAGE-seq across various human cell tissues.
DOI: 10.6084/m9.figshare.26992216.v1
title: Additional file 2 of BORIS/CTCFL epigenetically reprograms clustered CTCF binding sites into alternative transcriptional start sites

description: Additional file 2: Supplementary Table S1. A list of TSSs identified through CAGE-seq across various human cell tissues.
DOI: 10.6084/m9.figshare.26992219
title: Additional file 3 of BORIS/CTCFL epigenetically reprograms clustered CTCF binding sites into alternative transcriptional start sites

description: Additional file 3: Supplementary Table S2. The overlapping of BORIS binding sites identified in K562 cells with CAGE-seq data obtained from both K562 and testes samples.
DOI: 10.6084/m9.figshare.26992222
title: Additional file 4 of BORIS/CTCFL epigenetically reprograms clustered CTCF binding sites into alternative transcriptional start sites

description: Additional file 4: Supplementary Table S3. A list of newly identified transcripts in NIH3T3 cells.
DOI: 10.6084/m9.figshare.26992222.v1
title: Additional file 4 of BORIS/CTCFL epigenetically reprograms clustered CTCF binding sites into alternative transcriptional start sites

description: Additional file 4: Supplementary Table S3. A list of newly identified transcripts in NIH3T3 cells.
DOI: 10.6084/m9.figshare.26992225
title: Additional file 5 of BORIS/CTCFL epigenetically reprograms clustered CTCF binding sites into alternative transcriptional start sites

description: Additional file 5: Supplementary Table S4. A list of pathways deregulated upon ectopic BORIS expression in NIH3T3 cells.
DOI: 10.6084/m9.figshare.26992231
title: Additional file 6 of BORIS/CTCFL epigenetically reprograms clustered CTCF binding sites into alternative transcriptional start sites

description: Additional file 6: Supplementary Table S5. A list of significantly enriched transcription factor (TF) binding motifs at CTCF/BORIS binding sites converted into active promoters.
DOI: 10.6084/m9.figshare.26992231.v1
title: Additional file 6 of BORIS/CTCFL epigenetically reprograms clustered CTCF binding sites into alternative transcriptional start sites

description: Additional file 6: Supplementary Table S5. A list of significantly enriched transcription factor (TF) binding motifs at CTCF/BORIS binding sites converted into active promoters.
DOI: 10.6084/m9.figshare.26992234
title: Additional file 7 of BORIS/CTCFL epigenetically reprograms clustered CTCF binding sites into alternative transcriptional start sites

description: Additional file 7: Supplementary Table S6. A list of all NGS data generated in this study.
DOI: 10.6084/m9.figshare.26992234.v1
title: Additional file 7 of BORIS/CTCFL epigenetically reprograms clustered CTCF binding sites into alternative transcriptional start sites

description: Additional file 7: Supplementary Table S6. A list of all NGS data generated in this study.
DOI: 10.6084/m9.figshare.26992294
title: Additional file 6 of Process evaluation of school-based high-intensity interval training interventions for children and adolescents: a systematic review and meta-analysis of randomized controlled trials

description: Additional file 6.
DOI: 10.6084/m9.figshare.26992294.v1
title: Additional file 6 of Process evaluation of school-based high-intensity interval training interventions for children and adolescents: a systematic review and meta-analysis of randomized controlled trials

description: Additional file 6.
DOI: 10.6084/m9.figshare.26992303
title: Additional file 2 of Mapping the functional impact of non-coding regulatory elements in primary T cells through single-cell CRISPR screens

description: Additional file 2: Table S1. Target selecion and gRNA library information. Coordinates are based on the human reference genome (GRCh38). For positive control targets, the expected gene is indicated.
DOI: 10.6084/m9.figshare.26992303.v1
title: Additional file 2 of Mapping the functional impact of non-coding regulatory elements in primary T cells through single-cell CRISPR screens

description: Additional file 2: Table S1. Target selecion and gRNA library information. Coordinates are based on the human reference genome (GRCh38). For positive control targets, the expected gene is indicated.
DOI: 10.6084/m9.figshare.26992306
title: Additional file 3 of Mapping the functional impact of non-coding regulatory elements in primary T cells through single-cell CRISPR screens

description: Additional file 3: Table S2. MAST differential expression results for all genes within 1Mb of a perturbation and detected in at least 5% of cells. Results are aggregated at the target level.
DOI: 10.6084/m9.figshare.26992306.v1
title: Additional file 3 of Mapping the functional impact of non-coding regulatory elements in primary T cells through single-cell CRISPR screens

description: Additional file 3: Table S2. MAST differential expression results for all genes within 1Mb of a perturbation and detected in at least 5% of cells. Results are aggregated at the target level.
DOI: 10.6084/m9.figshare.26992309
title: Additional file 4 of Mapping the functional impact of non-coding regulatory elements in primary T cells through single-cell CRISPR screens

description: Additional file 4: Table S3. Differential gene expression analysis of bulk RNA-seq data from the E2G validation experiments.
DOI: 10.6084/m9.figshare.26992309.v1
title: Additional file 4 of Mapping the functional impact of non-coding regulatory elements in primary T cells through single-cell CRISPR screens

description: Additional file 4: Table S3. Differential gene expression analysis of bulk RNA-seq data from the E2G validation experiments.
DOI: 10.6084/m9.figshare.26992318
title: Additional file 1 of Biological basis of extensive pleiotropy between blood traits and cancer risk

description: Additional file 1: Table S1. Blood traits, cancer types and GWAS data sources. Table S2. Plasma samples of women carriers of pathogenic variants in BRCA1/2, affected or unaffected by breast cancer after blood test (&lt; 12 months) and used for circulating sRNA-seq. Table S3. Plasma samples of sporadic women affected or unaffected by breast cancer after blood test (&lt; 12 months) and used for sRNA-seq. Table S4. Multivariate Cox regression analysis of cancer diagnosis in UKBB (all cancers; &gt;12 months from basal blood test). Table S5. Multivariate Cox regression analysis of cancer diagnosis in UKBB (all cancers; within 12 months from basal blood test). Table S6. Multivariate Cox regression analysis of cancer diagnosis in women of the UKBB (all cancers; &gt;12 months from basal blood test). Table S7. Multivariate Cox regression analysis of cancer diagnosis in men of the UKBB (all cancers; &gt;12 months from basal blood test). Table S8. Patient and incident cases included in the analyses. Table S9. Multivariate Cox regression analysis of breast cancer diagnosis in UKBB (&gt;12 months from basal blood test). Table S10. Multivariate Cox regression analysis of colon cancer diagnosis in UKBB (&gt;12 months from basal blood test). Table S11. Multivariate Cox regression analysis of lung cancer diagnosis in UKBB (&gt;12 months from basal blood test). Table S12. Multivariate Cox regression analysis of prostate cancer diagnosis in UKBB (&gt;12 months from basal blood test). Table S13. Heritability and genetic correlations between blood cell traits and cancer risk. Table S14. Genomic inflation (lambda factor) analysis for the comparisons between cancer risk and blood trait GWAS results. Table S15. Pleiotropy leading SNPs linking blood traits and cancer risk. Table S16. Pan-cancer pleiotropic SNPs (Rashkin et al., 2020) identified in the blood-cancer pleiotropy study (conjFDR &lt; 0.05). Table S17. Pleiotropic gene candidates previously associated with leukocyte telomere length (Codd et al., 2021). Table S18. Genomic hotspots (1, 3, or 5 Mb) with significant enrichment in pleiotropic variants and linked to &gt; 2 cancer traits. Table S19. Regulatory marks enriched in the blood-cancer pleiotropic variants (DNAse I hypersensitivity (sheffield_dnase), transcription factor binding sites (encode_tfbs), and epigenetic marks (oadmap_epigenomics) data). Table S20. Master regulators of hematopoiesis. Table S21. Pleiotropic gene candidates identified in the hematopoiesis-related gene modules (Velten et al., 2017). Table S22. Pleiotropic variants linked to RNY-containing loci. Table S23. GWAS-catalog cancer risk associations linked to RNY-containing loci (chromosomes 1-22). Table S24. Regulatory marks enriched in the 5' and 3' TSS regions of the pleiotropic RNY relative to non-pleiotropic RNY loci. Table S25. SLE risk variants (GWAS) correlated with blood-cancer pleiotropic variants in RNY-containing loci.
DOI: 10.6084/m9.figshare.26992318.v1
title: Additional file 1 of Biological basis of extensive pleiotropy between blood traits and cancer risk

description: Additional file 1: Table S1. Blood traits, cancer types and GWAS data sources. Table S2. Plasma samples of women carriers of pathogenic variants in BRCA1/2, affected or unaffected by breast cancer after blood test (&lt; 12 months) and used for circulating sRNA-seq. Table S3. Plasma samples of sporadic women affected or unaffected by breast cancer after blood test (&lt; 12 months) and used for sRNA-seq. Table S4. Multivariate Cox regression analysis of cancer diagnosis in UKBB (all cancers; &gt;12 months from basal blood test). Table S5. Multivariate Cox regression analysis of cancer diagnosis in UKBB (all cancers; within 12 months from basal blood test). Table S6. Multivariate Cox regression analysis of cancer diagnosis in women of the UKBB (all cancers; &gt;12 months from basal blood test). Table S7. Multivariate Cox regression analysis of cancer diagnosis in men of the UKBB (all cancers; &gt;12 months from basal blood test). Table S8. Patient and incident cases included in the analyses. Table S9. Multivariate Cox regression analysis of breast cancer diagnosis in UKBB (&gt;12 months from basal blood test). Table S10. Multivariate Cox regression analysis of colon cancer diagnosis in UKBB (&gt;12 months from basal blood test). Table S11. Multivariate Cox regression analysis of lung cancer diagnosis in UKBB (&gt;12 months from basal blood test). Table S12. Multivariate Cox regression analysis of prostate cancer diagnosis in UKBB (&gt;12 months from basal blood test). Table S13. Heritability and genetic correlations between blood cell traits and cancer risk. Table S14. Genomic inflation (lambda factor) analysis for the comparisons between cancer risk and blood trait GWAS results. Table S15. Pleiotropy leading SNPs linking blood traits and cancer risk. Table S16. Pan-cancer pleiotropic SNPs (Rashkin et al., 2020) identified in the blood-cancer pleiotropy study (conjFDR &lt; 0.05). Table S17. Pleiotropic gene candidates previously associated with leukocyte telomere length (Codd et al., 2021). Table S18. Genomic hotspots (1, 3, or 5 Mb) with significant enrichment in pleiotropic variants and linked to &gt; 2 cancer traits. Table S19. Regulatory marks enriched in the blood-cancer pleiotropic variants (DNAse I hypersensitivity (sheffield_dnase), transcription factor binding sites (encode_tfbs), and epigenetic marks (oadmap_epigenomics) data). Table S20. Master regulators of hematopoiesis. Table S21. Pleiotropic gene candidates identified in the hematopoiesis-related gene modules (Velten et al., 2017). Table S22. Pleiotropic variants linked to RNY-containing loci. Table S23. GWAS-catalog cancer risk associations linked to RNY-containing loci (chromosomes 1-22). Table S24. Regulatory marks enriched in the 5' and 3' TSS regions of the pleiotropic RNY relative to non-pleiotropic RNY loci. Table S25. SLE risk variants (GWAS) correlated with blood-cancer pleiotropic variants in RNY-containing loci.
DOI: 10.6084/m9.figshare.26992594
title: Additional file 71 of Single-cell RNA sequencing of mid-to-late stage spider embryos: new insights into spider development

description: Additional file 71.
DOI: 10.6084/m9.figshare.26992594.v1
title: Additional file 71 of Single-cell RNA sequencing of mid-to-late stage spider embryos: new insights into spider development

description: Additional file 71.
DOI: 10.6084/m9.figshare.26992600
title: Additional file 72 of Single-cell RNA sequencing of mid-to-late stage spider embryos: new insights into spider development

description: Additional file 72.
DOI: 10.6084/m9.figshare.26992600.v1
title: Additional file 72 of Single-cell RNA sequencing of mid-to-late stage spider embryos: new insights into spider development

description: Additional file 72.
DOI: 10.6084/m9.figshare.26992603
title: Additional file 73 of Single-cell RNA sequencing of mid-to-late stage spider embryos: new insights into spider development

description: Additional file 73.
DOI: 10.6084/m9.figshare.26992603.v1
title: Additional file 73 of Single-cell RNA sequencing of mid-to-late stage spider embryos: new insights into spider development

description: Additional file 73.
DOI: 10.6084/m9.figshare.26992609
title: Additional file 74 of Single-cell RNA sequencing of mid-to-late stage spider embryos: new insights into spider development

description: Additional file 74.
DOI: 10.6084/m9.figshare.26992609.v1
title: Additional file 74 of Single-cell RNA sequencing of mid-to-late stage spider embryos: new insights into spider development

description: Additional file 74.
DOI: 10.6084/m9.figshare.26992642
title: Additional file 2 of Convergent genomic signatures associated with vertebrate viviparity

description: Additional file 2: Table S1. Reproductive and genomic information for species included in this study.
DOI: 10.6084/m9.figshare.26992642.v1
title: Additional file 2 of Convergent genomic signatures associated with vertebrate viviparity

description: Additional file 2: Table S1. Reproductive and genomic information for species included in this study.
DOI: 10.6084/m9.figshare.26992654
title: Additional file 5 of Convergent genomic signatures associated with vertebrate viviparity

description: Additional file 5: Table S2. Correlation between protein family size and viviparity.
DOI: 10.6084/m9.figshare.26992654.v1
title: Additional file 5 of Convergent genomic signatures associated with vertebrate viviparity

description: Additional file 5: Table S2. Correlation between protein family size and viviparity.
DOI: 10.6084/m9.figshare.26992663
title: Additional file 8 of Convergent genomic signatures associated with vertebrate viviparity

description: Additional file 8: Table S3. Alignment statistics for whole-genome alignments generated using different alignment methods.
DOI: 10.6084/m9.figshare.26992663.v1
title: Additional file 8 of Convergent genomic signatures associated with vertebrate viviparity

description: Additional file 8: Table S3. Alignment statistics for whole-genome alignments generated using different alignment methods.
DOI: 10.15468/dl.2xrfcz
title: Occurrence Download

description: A dataset containing 34 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Tetrathemis flavescens Kirby, 1889)"
 ]
}

 The dataset includes 34 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010741-240425142415019/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.