cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25386/genetics.10247969.v1
title: Supplemental Material for Bhardwaj, Pandey, and Babu, 2020

description: Supplemental files and movies. <br>
DOI: 10.25386/genetics.10247969.v2
title: Supplemental Material for Bhardwaj, Pandey, and Babu, 2020

description: Supplemental files and movies. <br>
DOI: 10.25387/g3.9820622.v1
title: Supplement for Maduro, 2020

description: Files containing all predicted genes, DNA/protein sequence files used for alignments and phylogenetic trees, output of MEME searches, and Tables of results from simple site searches.<br>
DOI: 10.25386/genetics.8851346
title: Supplemental Material for Kushnir et al., 2020

description: Excessive RTK signaling, often caused by activating mutations in Ras, Raf and/or MEK, occurs in most human tumors. Intriguingly, confirmed cancer-driver mutations in the downstream effector kinase, ERK, have not been reported. To test if active ERK mutants can function as oncoproteins, we introduced an activating mutation, originally identified in a yeast ERK, into the single <i>Drosophila</i> ERK. We find that this mutation renders ERK catalytically active independently of upstream signaling, and that its expression induces extensive over-proliferation and hyperplastic tumor formation <i>in vivo</i>. Thus, some human ERK1/2 mutations identified in patient-derived tumours may actually represent overlooked oncogenic, cancer-causing mutations.<br>
DOI: 10.25386/genetics.8851346.v1
title: Supplemental Material for Kushnir et al., 2020

description: Excessive RTK signaling, often caused by activating mutations in Ras, Raf and/or MEK, occurs in most human tumors. Intriguingly, confirmed cancer-driver mutations in the downstream effector kinase, ERK, have not been reported. To test if active ERK mutants can function as oncoproteins, we introduced an activating mutation, originally identified in a yeast ERK, into the single <i>Drosophila</i> ERK. We find that this mutation renders ERK catalytically active independently of upstream signaling, and that its expression induces extensive over-proliferation and hyperplastic tumor formation <i>in vivo</i>. Thus, some human ERK1/2 mutations identified in patient-derived tumours may actually represent overlooked oncogenic, cancer-causing mutations.<br>
DOI: 10.25387/g3.10107011
title: Supplemental Material for Kurko et al., 2020

description: Figure S1 contains mRNA expression profiles of <i>six6a</i>-related genes in Atlantic salmon tissues. Table S1 contains<b> </b>Atlantic salmon tissues chosen for the study. Table S2 contains genes included in the study. Code used to analyze the mRNA expression data is provided in File S1.
DOI: 10.25387/g3.10107011.v1
title: Supplemental Material for Kurko et al., 2020

description: Figure S1 contains mRNA expression profiles of <i>six6a</i>-related genes in Atlantic salmon tissues. Table S1 contains<b> </b>Atlantic salmon tissues chosen for the study. Table S2 contains genes included in the study. Code used to analyze the mRNA expression data is provided in File S1.
DOI: 10.25387/g3.10310750
title: Supplemental Material for Yang et al., 2020

description: Table S1 contains information about DSRs in three compared groups. Within each sheet, the second column listed the start and the end position for identified DSRs; the third column and the fourth column showed the number of top SNPs in different levels; the last column only exhibited the candidate genes which contained the SNP located in gene area. Table S2-S4 contain information about the genes derived from DSRs and the GO enrichment in three compared groups. For each file, the first sheet showed all genes from DSRs within each group, and the rest sheets showed results of GO enrichment in 3 ontology, which were biological process, molecular function and cellular component, respectively. Every term listed in ontology was arranged with the value of Fold Enrichment, and we exhibited enriched genes within the top 10 terms. Figure S1-S2 are supplemental materials for STRUCTURE analysis.
DOI: 10.25387/g3.10310750.v1
title: Supplemental Material for Yang et al., 2020

description: Table S1 contains information about DSRs in three compared groups. Within each sheet, the second column listed the start and the end position for identified DSRs; the third column and the fourth column showed the number of top SNPs in different levels; the last column only exhibited the candidate genes which contained the SNP located in gene area. Table S2-S4 contain information about the genes derived from DSRs and the GO enrichment in three compared groups. For each file, the first sheet showed all genes from DSRs within each group, and the rest sheets showed results of GO enrichment in 3 ontology, which were biological process, molecular function and cellular component, respectively. Every term listed in ontology was arranged with the value of Fold Enrichment, and we exhibited enriched genes within the top 10 terms. Figure S1-S2 are supplemental materials for STRUCTURE analysis.
DOI: 10.25387/g3.9820622
title: Supplemental Material for Maduro, 2020

description: Files containing all predicted genes, DNA/protein sequence files used for alignments and phylogenetic trees, output of MEME searches, and Tables of results from simple site searches.<br>
DOI: 10.6084/m9.figshare.3761562.v1298
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.25387/g3.9820622.v2
title: Supplemental Material for Maduro, 2020

description: Files containing all predicted genes, DNA/protein sequence files used for alignments and phylogenetic trees, output of MEME searches, and Tables of results from simple site searches.<br>
DOI: 10.6084/m9.figshare.9119996.v2
title: Heavy-load resistance exercise during chemotherapy in physically inactive breast cancer survivors at risk for lymphedema: a randomized trial

description: <b>Background:</b> Due to long-standing concerns that heavy-load lifting could increase the risk of developing lymphedema, breast cancer survivors have been advised to refrain from resistance exercise with heavy loads. This study prospectively evaluated the effect of heavy-load resistance exercise on lymphedema development in women receiving chemotherapy for breast cancer. <b>Material and Methods:</b> Physically inactive women receiving adjuvant chemotherapy for breast cancer (<i>n</i> = 153) were randomized to a HIGH (supervised, multimodal exercise including heavy-load resistance exercise: 85–90% 1 repetition maximum [RM], three sets of 5–8 repetitions) versus LOW (pedometer and one-on-one consultations) 12-week intervention. Outcomes (baseline, 12 and 39 weeks) included lymphedema status (extracellular fluid [bioimpedance spectroscopy] and inter-arm volume % difference [dual-energy X-ray absorptiometry], lymphedema symptoms [numeric rating scale 0–10]), upper-extremity strength (1 RM), and quality of life domains (EORTC- BR23). Linear mixed models were used to evaluate equivalence between groups for lymphedema outcomes (equivalence margins for L-Dex, % difference and symptoms scale: ±5, ±3% and ±1, respectively). Superiority analysis was conducted for muscle strength and quality of life domains. <b>Results:</b> Postintervention equivalence between groups was found for extracellular fluid (0.4; 90% CI −2.5 to 3.2) and symptoms of heaviness (−0.2; −0.6 to 0.2), tightness (−0.1; −0.8 to 0.6) and swelling (0.2; −0.4 to 0.8). Nonequivalence was found for inter-arm volume % difference (−3.5%; −17.3 to 10.3) and pain (−0.7; −1.3 to 0), favoring HIGH. Strength gains were superior in the HIGH versus LOW group (3 kg; 1 to 5, <i>p</i> <b>Conclusion:</b> Findings suggest that physically inactive breast cancer survivors can benefit from supervised heavy-load resistance exercise during chemotherapy without increasing lymphedema risk. <b>Trial registration:</b> ISRCTN13816000
DOI: 10.25387/g3.8481641
title: Supplemental Material for Apuli et al., 2020

description: Supplementary methods for "Inferring the genomic landscape of recombination rate variation in European Aspen (<i>Populus tremula</i>)"
DOI: 10.25387/g3.7877543
title: Supplemental Material for Bhatnagar et al., 2020

description: Data associated with Bhatnagar et al., submitted to G3.
DOI: 10.25387/g3.7877543.v1
title: Supplemental Material for Bhatnagar et al., 2020

description: Data associated with Bhatnagar et al., submitted to G3.
DOI: 10.25387/g3.8481641.v1
title: Supplemental Material for Apuli et al., 2020

description: Supplementary methods for "Inferring the genomic landscape of recombination rate variation in European Aspen (<i>Populus tremula</i>)"
DOI: 10.25387/g3.7877543.v2
title: Supplemental Material for Bhatnagar et al., 2020

description: Data associated with Bhatnagar et al., submitted to G3.
DOI: 10.6084/m9.figshare.10318823.v3
title: Panel Discussion: Who's afraid of data misuse? #SciData19

description: Grace Baynes chairs the panel discussion entitled 'Who's afraid of data misuse?' at Better Science through Better Data 2019 (#SciData19). <br>The panelists are:<br>- Yves-Alexandre de Montjoye, Imperial College London- Sabina Leonelli, University of Exeter- Shelley Stall, American Geophysical Union<br>The video recording, live scribe illustrations plus Grace and Sabina's presentation slides are included.<br>
DOI: 10.6084/m9.figshare.3761562.v1299
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.8162009
title: Figure Data

description: TEM images of WT and A2AR primary chondrocytes
DOI: 10.6084/m9.figshare.8162009.v1
title: Figure Data

description: TEM images of WT and A2AR primary chondrocytes
DOI: 10.6084/m9.figshare.3761562.v1300
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.3761562.v1301
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.25387/g3.10284269
title: Supplemental Material for Shahandeh et al., 2020

description: Courtship frequency and effort data for <i>D. melanogaster </i>and <i>D. simulans </i>parent strains, their reciprocal hybrids, duplication hybrids, and <i>D. melanogaster </i>knock-out hybrids.
DOI: 10.25387/g3.10284269.v1
title: Supplemental Material for Shahandeh et al., 2020

description: Courtship frequency and effort data for <i>D. melanogaster </i>and <i>D. simulans </i>parent strains, their reciprocal hybrids, duplication hybrids, and <i>D. melanogaster </i>knock-out hybrids.
DOI: 10.25413/sun.10318163
title: Petrochemical blending problem instances

description: This collection supplies the input data for four petrochemical blending problems.
DOI: 10.25386/genetics.10566044
title: Supplemental Material for Macke et al., 2020

description: This file contains Figs S1 to S7 and Tables S1 to S4 as Supplementary Information.
DOI: 10.25386/genetics.10566044.v1
title: Supplemental Material for Macke et al., 2020

description: This file contains Figs S1 to S7 and Tables S1 to S4 as Supplementary Information.
DOI: 10.25387/g3.10251044.v2
title: Supplemental Material for Chhotaray et al., 2019

description: Supplementary sheet 1 contains details of Illumina sequencing library preparations and Bioinformatics analysis of sequencing data. Figure S1 contains the KEGG Classification annotation statistics of Mab<sup>S </sup>and Mab<sup>R</sup> whereas Figure S2 contains the COG classification annotation statistics of Mab<sup>S </sup>and Mab<sup>R</sup>. Figure S3 and Figure S4 contain the pan-genome and core genome phylogeny of 25 complete genome sequences of <i>M. abscessus </i>species respectively. Figure S5 contains gelelectrophoresis of plasmids extracted from <i>M. abscessus </i>clinical strains. Figure S6 contains the maps representing the circular visualization of insertions and deletions in Mab<sup>R</sup> (CP034191) and Mab<sup>S</sup> (CP034181). Table S1 contains the annotations and related data for linear plasmid pMabS_GZ002 gene. Table S2 contains the information about the variation in methylation sites in the genes of interest between two clinical strains of <i>M. abscessus</i>. Table S3.1, Table S3.2, and Table S3.2, contain the information about the gene content in the inserted and deleted regions (Reference vs Mab<sup>R</sup>), (Reference vs Mab<sup>S</sup>), (Mab<sup>S </sup>vs Mab<sup>R</sup>), respectively. Table S4 contains the information about the drug susceptibility of <i>M. abscessus</i> isolates.<b> </b>Table S5 contains statistics of PF data generated by Illumina sequencing. Table S6 contains the statistics of clean data after quality control. Table S7 contains the proportion of statistics of the clean data compared to PF data after quality control. Table S8 contains the genome alignment statistics of two <i>M. abscessus </i>clinical strains obtained from Illumina sequencing. Table S9 contains the raw reads statistics of two of <i>M. abscessus </i>clinical strains generated from single molecule Real-Time (SMRT) sequencing. Table S10 contains the genome assembly statistics of two <i>M. abscessus </i>clinical strains obtained from single molecule Real-Time (SMRT) sequencing. File Xls S1 contains<b> </b>result of structural variation analysis. File Xls S2 contains the information about the identified SNVs, each motif’s methylation site, methylation score, type of methylation, and all locations of discovered motifs in strains, motif information of pMabS_GZ002 plasmid, identified methyltransferase in both strains. File Xls S3 contains the statistics of the 25 available complete genomes of <i>M. abscessus </i>used for pan-genome analysis. File Xls S4 contains the statistics number of accessory genes, unique genes as well as exclusively absent genes determined among the <i>M. abscessus </i>species. MabS.h5 and MabR.h5 contain the raw files of methylome analysis of Mab<sup>S </sup>and MabR.h5, respectively.
DOI: 10.6084/m9.figshare.3761562.v1302
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.8192162.v2
title: SWAP70 is a universal GEF-like adaptor for tethering actin to phagosomes

description: We recently identified a key role for SWAP70 as the tethering factor stabilizing F-actin filaments on the surface of phagosomes in human dendritic cells by interacting both with Rho-family GTPases and the lipid phosphatidylinositol (3,4)-bisphosphate. In this study, we aimed to investigate whether this role of SWAP70 was general among immune phagocytes. Our data reveal that SWAP70 is recruited to early phagosomes of macrophages and dendritic cells from both human and mouse. The putative inhibitor of SWAP70 sanguinarine blocked phagocytosis and F-actin polymerization, supporting a key role for SWAP70 in phagocytosis as demonstrated previously with knock-down. Moreover, SWAP70 was recently shown to sequester the F-actin severing protein cofilin and we investigated this relationship in phagocytosis. Our data show an increased activation of cellular cofilin upon siRNA knockdown of SWAP70. Finally, we explored whether SWAP70 would be recruited to the immune synapse between dendritic cells and T cells required for antigen presentation, as the formation of such synapses depends on F-actin. However, we observed that SWAP70 was depleted at immune synapses and specifically was recruited to phagosomes. Our data support an essential and specific role for SWAP70 in tethering and stabilizing F-actin to the phagosomal surface in a wide range of phagocytes.
DOI: 10.25387/g3.10406519
title: Supplemental Material for Morton et al., 2020

description: Supplemental methods, figures, and tables accompanying Morton <i>et al</i>. manuscript "Challenges and Approaches to Genotyping Repetitive DNA" File S1 contains supplemental materials and methods and a list of tables Figure S1 contains Southern blots and ethidium bromide staining of CHEF gels Figure S2 contains droplet digital PCR condition optimization Figure S3 contains details of smMIP-based copy number estimation Figure S4 contains details of rDNA locus FISH characteristics for <i>C. elegans</i> strains Table S1 contains metrics from Nextera whole genome sequencing of <i>C. elegans</i> strains Table S2 contains percent error of rDNA copy number estimation for <i>C. elegans</i> strains Table S3 contains results of downsampling <i>C. elegans</i> WGS data Table S4 contains different aligner and trimming comparisons of <i>C. elegans</i> strains rDNA copy number estimate Table S5 contains coordinate of <i>C. elegans</i> single copy regions Table S6 contains WGS counts of <i>C. elegans</i> single copy regions Table S7 contains published yeast strain SRA numbers Table S8 contains yeast diploid strain rDNA estimates Table S9 contains yeast strain SNV genotyping Table S10 contains droplet digital PCR raw data Table S11 contains smMIP data Table S12 contains rDNA FISH summary cell counts Table S13 contains rDNA FISH data Table S14 contains sequences of oligos Table S15 contains band measurements from <i>C. elegans</i> CHEF gels
DOI: 10.25387/g3.10406519.v1
title: Supplemental Material for Morton et al., 2020

description: Supplemental methods, figures, and tables accompanying Morton <i>et al</i>. manuscript "Challenges and Approaches to Genotyping Repetitive DNA" File S1 contains supplemental materials and methods and a list of tables Figure S1 contains Southern blots and ethidium bromide staining of CHEF gels Figure S2 contains droplet digital PCR condition optimization Figure S3 contains details of smMIP-based copy number estimation Figure S4 contains details of rDNA locus FISH characteristics for <i>C. elegans</i> strains Table S1 contains metrics from Nextera whole genome sequencing of <i>C. elegans</i> strains Table S2 contains percent error of rDNA copy number estimation for <i>C. elegans</i> strains Table S3 contains results of downsampling <i>C. elegans</i> WGS data Table S4 contains different aligner and trimming comparisons of <i>C. elegans</i> strains rDNA copy number estimate Table S5 contains coordinate of <i>C. elegans</i> single copy regions Table S6 contains WGS counts of <i>C. elegans</i> single copy regions Table S7 contains published yeast strain SRA numbers Table S8 contains yeast diploid strain rDNA estimates Table S9 contains yeast strain SNV genotyping Table S10 contains droplet digital PCR raw data Table S11 contains smMIP data Table S12 contains rDNA FISH summary cell counts Table S13 contains rDNA FISH data Table S14 contains sequences of oligos Table S15 contains band measurements from <i>C. elegans</i> CHEF gels
DOI: 10.6084/m9.figshare.3761562.v1303
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.3761562.v1304
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.25386/genetics.11106125.v1
title: Supplemental Material for Bijma, Wientjes and Calus, 2020

description: This file contains- R-codes used for simulation- Supplementary Tables S1 and S2- Excel File with empirical regression coefficients
DOI: 10.25387/g3.10423904
title: Supplemental Material for Randhawa et al., 2020

description: <b>Table S1</b> Comparison of SNP-based current poll testing (CPT) and the optimized poll testing (OPT) assays on 20,636 samples for the frequency of “No results” in various cattle breeds. <b><br></b><b>Table S2</b> List of 14 microsatellites mapped within the Poll locus on chromosome 1. <b><br></b><b>Table S3</b> Call rate of 10 SNPs in different cattle breeds and cross-bred populations. <b><br></b><b>Table S4</b> Results of targeted DNA sequences of 55 Brahman samples showing 60bp genome region around SNP rs800947704[C/T=Y] (marked as 0) and upstream variant SNP rs381418143 [A/G=R] (marked as -3). Two types of errors were observed in the genotyping assays, 1: genotype failed (--) when -3=G (yellow highlights), 2: wrong genotypes when -3=R and 0=Y (purple highlights). <b><br></b><b>Figure S1</b> Distribution (%) of MSAT and SNP based poll gene testing results for Horned (HH), Hybrid (HP), Polled (PP) and failing (“Not Determined” or “No Results” ) samples across 10 Australian beef breeds (n=16,941). <b><br></b><b>Figure S2</b> Breed-wise distribution (%) of Optimized Poll Testing (OPT) assay results (HH = Horned, HP = Hybrids, PP = Polled, No Results = Failed assay) in first column and Allele Frequencies (AF) of Horn (H), Poll-Celtic (P<sub>C</sub>) and Poll-Friesian (P<sub>F</sub>) mutations in column 2 across ten Australian beef breeds (n = 16,903). Note that presence of H alleles in Angus and P<sub>C</sub>/P<sub>F</sub> alleles in Wagyu is indicative of cross-bred individuals. Overall, the results show that polled animals of Australian beef breeds predominantly carry P<sub>C</sub> as compared to P<sub>F</sub>, except for Shorthorn. <b><br></b><b>Data 1</b> Validation population phenotypes and Poll markers genotypes data file: Data_1_project_validation_populations_phenotypes_and_poll_locus_SNPs.csv <b><br></b><b>Data 2 </b>Commercial population Poll markers genotypes and BREEDPLAN phenotypes data file: Data_2_project_poll_locus_10_SNPs_genotypes_and_BREEDPLAN_phenotypes.csv
DOI: 10.25387/g3.10423904.v1
title: Supplemental Material for Randhawa et al., 2020

description: <b>Table S1</b> Comparison of SNP-based current poll testing (CPT) and the optimized poll testing (OPT) assays on 20,636 samples for the frequency of “No results” in various cattle breeds. <b><br></b><b>Table S2</b> List of 14 microsatellites mapped within the Poll locus on chromosome 1. <b><br></b><b>Table S3</b> Call rate of 10 SNPs in different cattle breeds and cross-bred populations. <b><br></b><b>Table S4</b> Results of targeted DNA sequences of 55 Brahman samples showing 60bp genome region around SNP rs800947704[C/T=Y] (marked as 0) and upstream variant SNP rs381418143 [A/G=R] (marked as -3). Two types of errors were observed in the genotyping assays, 1: genotype failed (--) when -3=G (yellow highlights), 2: wrong genotypes when -3=R and 0=Y (purple highlights). <b><br></b><b>Figure S1</b> Distribution (%) of MSAT and SNP based poll gene testing results for Horned (HH), Hybrid (HP), Polled (PP) and failing (“Not Determined” or “No Results” ) samples across 10 Australian beef breeds (n=16,941). <b><br></b><b>Figure S2</b> Breed-wise distribution (%) of Optimized Poll Testing (OPT) assay results (HH = Horned, HP = Hybrids, PP = Polled, No Results = Failed assay) in first column and Allele Frequencies (AF) of Horn (H), Poll-Celtic (P<sub>C</sub>) and Poll-Friesian (P<sub>F</sub>) mutations in column 2 across ten Australian beef breeds (n = 16,903). Note that presence of H alleles in Angus and P<sub>C</sub>/P<sub>F</sub> alleles in Wagyu is indicative of cross-bred individuals. Overall, the results show that polled animals of Australian beef breeds predominantly carry P<sub>C</sub> as compared to P<sub>F</sub>, except for Shorthorn. <b><br></b><b>Data 1</b> Validation population phenotypes and Poll markers genotypes data file: Data_1_project_validation_populations_phenotypes_and_poll_locus_SNPs.csv <b><br></b><b>Data 2 </b>Commercial population Poll markers genotypes and BREEDPLAN phenotypes data file: Data_2_project_poll_locus_10_SNPs_genotypes_and_BREEDPLAN_phenotypes.csv