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Who produced the data? The data has been created by the authors listed above. Is the title specific enough? "Datasets related to a study aimed to identify genetic markers of CDA by subphenotypes associated with cardiotoxicity." Why has the data been created? These datasets are supplementary material with which the principal and supplementary figures and tables of our indicated work were generated. What limitations do the data have (for example, sensitive data has been deleted)? All confidential patient information is not present. We have not had access to that information, following current legal regulations. How should the data be interpreted? These data sets should not be separated from the main article in which they were utilized. Thus, to better understand their context, researchers should see them in the global scenario of our work. Are there gaps in the data, or do they give a complete picture of the topic studied? As indicated above, data should be considered and interpreted in the global context of our study. What processes have generated the data? The processes that generated the data are indicated in the summary of the data above and individually for each of them. Thus, each dataset is accompanied by a legend within the document. What does the data measure in the columns of the files? As indicated, each dataset individually shows the information contained in the legend of each dataset. What software is required to be able to read the data? The datasets are in Excel format. How should the data be quoted? Researchers should cite the data in the context of the work they belong to once it is published and free of the embargo. Can the data be reused? What use licenses are assigned to you? In principle, yes. If additional clinical information is required, these data were previously published by some of us, and the references are included in our manuscript. These data are available from the principal investigators of the references listed in our work upon reasonable request. Are there more versions of the data? Where? I do not think so beyond our files and copies. Have the technical terms and acronyms referenced by the data been defined? A legend with the appropriate descriptions accompanies each dataset. Have the geographic and chronological parameters of the data been qualified? The authors of the work have generated the data. Elsewhere, we indicate the authors of the work, their contributions, and affiliations. Are keywords sufficiently data-specific? Are they based on any thesaurus? Keywords are based on our study. We include cardiotoxicity due to anthracyclines, missing heritability, subphenotype, pathophenotype, complex trait. What is the name of the research project in which the data are framed? The main research project in which the data is prepared is: Títle: "Chemotherapy cardiotoxicity in the elderly: a translational and personnel approach." Ref.: PIE14/00066 Who has financed data production and management? Each of the authors of the study has its funding. The grants are included in the acknowledgments section of our manuscript., The data were created over the last six years during the achievement of this project., Here we present a series of supplemental datasets that complement our study entitled "A Systems Genetics approach to identify genetic markers of cardiotoxicity due to anthracyclines in cancer patients." The datasets presented here were used to generate the main and supplementary figures and tables of the indicated study. The study consists of the identification of genetic markers of cardiotoxicity due to anthracyclines (CDA). CDA is a complex genesis disease or complex trait, and because of this, there is a component of missing heritability. Therefore, it is not possible to identify genetic markers associated with CDA risk. Here, we propose that molecular subphenotypes associated with the CDA may be a strategy for identifying some of this missing heritability and risk markers associated with it. A similar strategy could be applied to identify markers of other diseases of complex genesis. This study is done using a genetically heterogeneous cohort of mice that developed breast cancer and was treated with doxorubicin or a combined treatment of doxorubicin and docetaxel. The mouse cohort was generated by backcrossing, so each mouse is genetically unique. Post-chemotherapy heart damage was assessed by quantifying fibrosis's cardiac area and the thickness of myocardial fibers. The genetic regions associated with CDA were assessed by massive genotyping and genetic linkage analysis. Several molecular subphenotypes were quantified in the myocardium, and their association with the CDA was evaluated. Subsequently, we identified which of them were most statistically associated with CDA in multivariate models. Moreover, which complex trait loci (QTLs) associated with molecular subphenotypes best explained CDA. This strategy served to identify in the cohort of mice genes whose allelic forms could be candidates for the risk of CDA. Allelic variants of these genes were evaluated in four cohorts of cancer patients treated with anthracyclines and whose CDA was evaluated by echocardiography or cardiac magnetic resonance imaging (CMR)., JPL laboratory was partially supported by the European Regional Development Fund (ERDF) and the Ministry of Science, Innovation, and Universities (SAF2014-56989-R, SAF2017-88854R), the Carlos III Health Institute (PIE14/00066), "Proyectos Integrados IBSAL 2015" (IBY15/00003), the Regional Government of Castile and Leon (CSI234P18), and "We can be heroes" Foundation. AGN laboratory and human patients' study are supported by funds from the ISCIII project grant (PI18/01242). The Human Genotyping unit is a member of CeGen, PRB3, and is supported by grant PT17/0019, of the PE I+D+i 2013-2016, funded by ISCIII and ERDF. SCLL was the recipient of a Ramón y Cajal research contract from the Spanish Ministry of Economy and Competitiveness, and the work was supported by MINECO/FEDER research grants (RTI2018-094130-B-100). The Proteomics Unit belongs to ProteoRed, PRB3-ISCIII, supported by grant PT17/0019/0023, of the PE I + D + I 2017-2020, funded by ISCIII and FEDER. RCC is funded by fellowships from the Spanish Regional Government of Castile and León. NGS is a recipient of an FPU fellowship (MINECO/FEDER). hiPSC-CM studies were funded in part by the "la Caixa" Banking Foundation under the project code HR18-00304" and Severo Ochoa CNIC Intramural Project (Expediente 12-2016 IGP) to JJ., Supplemental Dataset 1: CDA pathophenotypes after doxorubicin treatment. We treated 71 mice carrying breast cancer with doxorubicin. Each mouse was generated by backcrossing; thus, each one is genetically unique. Cardiotoxicity due to anthracyclines (CDA) was evaluated by automatically quantifying the heart fibrosis area and the average area of myocardial fibers as pathophenotypes of cardiotoxicity using the Ariol slide scanner. The histopathological damage was evaluated in the subendocardium and subepicardium from five randomly chosen regions of each sample (averages in μm2 are shown).-- Supplemental Dataset 2: CDA pathophenotypes after the combined therapy. We treated 61 mice carrying breast cancer with the combined therapy with doxorubicin and docetaxel. Each mouse was generated by backcrossing; thus, each one is genetically unique. Cardiotoxicity due to anthracyclines (CDA) was evaluated by automatically quantifying the heart fibrosis area and the average area of myocardial fibers as pathophenotypes of cardiotoxicity using the Ariol slide scanner. The histopathological damage was evaluated in the subendocardium and subepicardium from five randomly chosen regions of each sample (averages in μm2 are shown).-- Supplemental Dataset 3: CDA subphenotypes after doxorubicin therapy. Myocardium molecular subphenotypes after doxorubicin therapy. Proteins were quantified by a multiplex bead array (Luminex). TGFβ units are shown in pg/mL. The rest of the protein levels are shown in molecular fluorescence intensity (MFI) Units. The telomeric length was quantified by QPCR (RQ units). miRNAs were quantified by QPCR (RQ units). QPCR analyses were assessed by the ΔΔCT method; we show the averages of triplicates.-- Supplemental Dataset 4: CDA subphenotypes after the combined therapy. Myocardium molecular subphenotypes after the combined therapy with doxorubicin and docetaxel. Proteins were quantified by a multiplex bead array (Luminex). TGFβ units are shown in pg/mL. The rest of the protein levels are shown in molecular fluorescence intensity (MFI) Units. The telomeric length was quantified by QPCR (RQ units). miRNAs were quantified by QPCR (RQ units). QPCR analyses were assessed by the ΔΔCT method; we show the averages of triplicates.-- Supplemental Dataset 5: Correlations identified between molecular subphenotype levels in the myocardium and pathophenotypes of cardiotoxicity due to anthracyclines (CDA) after doxorubicin therapy in all mice.-- Supplemental Dataset 6: Correlations identified between molecular subphenotype levels in the myocardium and pathophenotypes of cardiotoxicity due to anthracyclines (CDA) after doxorubicin therapy in young mice. Correlation of Spearman.-- Supplemental Dataset 7: Correlations identified between molecular subphenotype levels in the myocardium and pathophenotypes of cardiotoxicity due to anthracyclines (CDA) after doxorubicin therapy in old mice. Correlation of Spearman.-- Supplemental Dataset 8: Correlations identified between molecular subphenotype levels in the myocardium and pathophenotypes of cardiotoxicity due to anthracyclines (CDA) after the combined therapy in all mice. Correlation of Spearman.-- Supplemental Dataset 9: Correlations identified between molecular subphenotype levels in the myocardium and pathophenotypes of cardiotoxicity due to anthracyclines (CDA) after the combined therapy in young mice. Correlation of Spearman.-- Supplemental Dataset 10: Correlations identified between molecular subphenotype levels in the myocardium and pathophenotypes of cardiotoxicity due to anthracyclines (CDA) after the combined therapy in old mice. Correlation of Spearman.-- Supplemental Dataset 11: Linkage analysis of molecular subphenotype levels quantified in the myocardium. Lod scores after doxorubicin therapy in all mice. The Illumina Mouse Medium Density Linkage Panel Assay was used to genotype 130 F1BX mice at 1449 single nucleotide polymorphisms (SNPs). Genotypes were classified as FVB/FVB (F/F) or FVB/C57BL/6 (F/B). Ultimately, 806 SNPs are informative from the FVB and C57BL/6 mice; the average genomic distance between these SNPs was 9.9 Mb. The genotype proportion among the F1BX mice showed a normal distribution. Linkage analysis was carried out using interval mapping with the expectation-maximization (EM) algorithm and R/QTL software. The criteria for significant and suggestive linkages for single markers were chosen based on Lander and Kruglyak (see methods section of our manuscript).-- Supplemental Dataset 12: Linkage analysis of molecular subphenotype levels quantified in the myocardium. Lod scores after doxorubicin therapy in young mice. The Illumina Mouse Medium Density Linkage Panel Assay was used to genotype 130 F1BX mice at 1449 single nucleotide polymorphisms (SNPs). Genotypes were classified as FVB/FVB (F/F) or FVB/C57BL/6 (F/B). Ultimately, 806 SNPs are informative from the FVB and C57BL/6 mice; the average genomic distance between these SNPs was 9.9 Mb. The genotype proportion among the F1BX mice showed a normal distribution. Linkage analysis was carried out using interval mapping with the expectation-maximization (EM) algorithm and R/QTL software. The criteria for significant and suggestive linkages for single markers were chosen based on Lander and Kruglyak (see methods section of our manuscript).-- Supplemental Dataset 13: Linkage analysis of molecular subphenotype levels quantified in the myocardium. Lod scores after doxorubicin therapy in old mice. The Illumina Mouse Medium Density Linkage Panel Assay was used to genotype 130 F1BX mice at 1449 single nucleotide polymorphisms (SNPs). Genotypes were classified as FVB/FVB (F/F) or FVB/C57BL/6 (F/B). Ultimately, 806 SNPs are informative from the FVB and C57BL/6 mice; the average genomic distance between these SNPs was 9.9 Mb. The genotype proportion among the F1BX mice showed a normal distribution. Linkage analysis was carried out using interval mapping with the expectation-maximization (EM) algorithm and R/QTL software. The criteria for significant and suggestive linkages for single markers were chosen based on Lander and Kruglyak (see methods section of our manuscript).-- Supplemental Dataset 14: Linkage analysis of molecular subphenotype levels quantified in the myocardium. Lod scores after the combined therapy in all mice. The Illumina Mouse Medium Density Linkage Panel Assay was used to genotype 130 F1BX mice at 1449 single nucleotide polymorphisms (SNPs). Genotypes were classified as FVB/FVB (F/F) or FVB/C57BL/6 (F/B). Ultimately, 806 SNPs are informative from the FVB and C57BL/6 mice; the average genomic distance between these SNPs was 9.9 Mb. The genotype proportion among the F1BX mice showed a normal distribution. Linkage analysis was carried out using interval mapping with the expectation-maximization (EM) algorithm and R/QTL software. The criteria for significant and suggestive linkages for single markers were chosen based on Lander and Kruglyak (see methods section of our manuscript).-- Supplemental Dataset 15: Linkage analysis of molecular subphenotype levels quantified in the myocardium. Lod scores after the combined therapy in young mice. The Illumina Mouse Medium Density Linkage Panel Assay was used to genotype 130 F1BX mice at 1449 single nucleotide polymorphisms (SNPs). Genotypes were classified as FVB/FVB (F/F) or FVB/C57BL/6 (F/B). Ultimately, 806 SNPs are informative from the FVB and C57BL/6 mice; the average genomic distance between these SNPs was 9.9 Mb. The genotype proportion among the F1BX mice showed a normal distribution. Linkage analysis was carried out using interval mapping with the expectation-maximization (EM) algorithm and R/QTL software. The criteria for significant and suggestive linkages for single markers were chosen based on Lander and Kruglyak (see methods section of our manuscript).-- Supplemental Dataset 16: Linkage analysis of molecular subphenotype levels quantified in the myocardium. Lod scores after the combined therapy in old mice. The Illumina Mouse Medium Density Linkage Panel Assay was used to genotype 130 F1BX mice at 1449 single nucleotide polymorphisms (SNPs). Genotypes were classified as FVB/FVB (F/F) or FVB/C57BL/6 (F/B). Ultimately, 806 SNPs are informative from the FVB and C57BL/6 mice; the average genomic distance between these SNPs was 9.9 Mb. The genotype proportion among the F1BX mice showed a normal distribution. Linkage analysis was carried out using interval mapping with the expectation-maximization (EM) algorithm and R/QTL software. The criteria for significant and suggestive linkages for single markers were chosen based on Lander and Kruglyak (see methods section of our manuscript).-- Supplemental Dataset 17: Massive genotyping of mouse cohort treated with doxorubicin. The genome-wide scan was carried out at the Spanish National Centre of Genotyping (CeGEN) at the Spanish National Cancer Research Centre (CNIO, Madrid, Spain). The Illumina Mouse Medium Density Linkage Panel Assay was used to genotype 130 F1BX mice at 1449 single nucleotide polymorphisms (SNPs). Genotypes were classified as FVB/FVB (F/F) or FVB/C57BL/6 (F/B). Ultimately, 806 SNPs are informative from the FVB and C57BL/6 mice; the average genomic distance between these SNPs was 9.9 Mb. The genotype proportion among the F1BX mice showed a normal distribution.-- Supplemental Dataset 18: Massive genotyping of mouse cohort treated with the combined therapy. The genome-wide scan was carried out at the Spanish National Centre of Genotyping (CeGEN) at the Spanish National Cancer Research Centre (CNIO, Madrid, Spain). The Illumina Mouse Medium Density Linkage Panel Assay was used to genotype 130 F1BX mice at 1449 single nucleotide polymorphisms (SNPs). Genotypes were classified as FVB/FVB (F/F) or FVB/C57BL/6 (F/B). Ultimately, 806 SNPs are informative from the FVB and C57BL/6 mice; the average genomic distance between these SNPs was 9.9 Mb. The genotype proportion among the F1BX mice showed a normal distribution.-- Supplemental Dataset 19: Linkage analysis of CDA pathophenotypes quantified in the myocardium. Lod scores after doxorubicin therapy in all mice. The Illumina Mouse Medium Density Linkage Panel Assay was used to genotype 130 F1BX mice at 1449 single nucleotide polymorphisms (SNPs). Genotypes were classified as FVB/FVB (F/F) or FVB/C57BL/6 (F/B). Ultimately, 806 SNPs are informative from the FVB and C57BL/6 mice; the average genomic distance between these SNPs was 9.9 Mb. The genotype proportion among the F1BX mice showed a normal distribution. Linkage analysis was carried out using interval mapping with the expectation-maximization (EM) algorithm and R/QTL software. The criteria for significant and suggestive linkages for single markers were chosen based on Lander and Kruglyak (see methods section of our manuscript).-- Supplemental Dataset 20: Linkage analysis of CDA pathophenotypes quantified in the myocardium. Lod scores after doxorubicin therapy in young mice. The Illumina Mouse Medium Density Linkage Panel Assay was used to genotype 130 F1BX mice at 1449 single nucleotide polymorphisms (SNPs). Genotypes were classified as FVB/FVB (F/F) or FVB/C57BL/6 (F/B). Ultimately, 806 SNPs are informative from the FVB and C57BL/6 mice; the average genomic distance between these SNPs was 9.9 Mb. The genotype proportion among the F1BX mice showed a normal distribution. Linkage analysis was carried out using interval mapping with the expectation-maximization (EM) algorithm and R/QTL software. The criteria for significant and suggestive linkages for single markers were chosen based on Lander and Kruglyak (see methods section of our manuscript).-- Supplemental Dataset 21: Linkage analysis of CDA pathophenotypes quantified in the myocardium. Lod scores after doxorubicin therapy in old mice. The Illumina Mouse Medium Density Linkage Panel Assay was used to genotype 130 F1BX mice at 1449 single nucleotide polymorphisms (SNPs). Genotypes were classified as FVB/FVB (F/F) or FVB/C57BL/6 (F/B). Ultimately, 806 SNPs are informative from the FVB and C57BL/6 mice; the average genomic distance between these SNPs was 9.9 Mb. The genotype proportion among the F1BX mice showed a normal distribution. Linkage analysis was carried out using interval mapping with the expectation-maximization (EM) algorithm and R/QTL software. The criteria for significant and suggestive linkages for single markers were chosen based on Lander and Kruglyak (see methods section of our manuscript).-- Supplemental Dataset 22: Linkage analysis of CDA pathophenotypes quantified in the myocardium. Lod scores after the combined therapy in all mice. The Illumina Mouse Medium Density Linkage Panel Assay was used to genotype 130 F1BX mice at 1449 single nucleotide polymorphisms (SNPs). Genotypes were classified as FVB/FVB (F/F) or FVB/C57BL/6 (F/B). Ultimately, 806 SNPs are informative from the FVB and C57BL/6 mice; the average genomic distance between these SNPs was 9.9 Mb. The genotype proportion among the F1BX mice showed a normal distribution. Linkage analysis was carried out using interval mapping with the expectation-maximization (EM) algorithm and R/QTL software. The criteria for significant and suggestive linkages for single markers were chosen based on Lander and Kruglyak (see methods section of our manuscript).-- Supplemental Dataset 23: Linkage analysis of CDA pathophenotypes quantified in the myocardium. Lod scores after the combined therapy in young mice. The Illumina Mouse Medium Density Linkage Panel Assay was used to genotype 130 F1BX mice at 1449 single nucleotide polymorphisms (SNPs). Genotypes were classified as FVB/FVB (F/F) or FVB/C57BL/6 (F/B). Ultimately, 806 SNPs are informative from the FVB and C57BL/6 mice; the average genomic distance between these SNPs was 9.9 Mb. The genotype proportion among the F1BX mice showed a normal distribution. Linkage analysis was carried out using interval mapping with the expectation-maximization (EM) algorithm and R/QTL software. The criteria for significant and suggestive linkages for single markers were chosen based on Lander and Kruglyak (see methods section of our manuscript).-- Supplemental Dataset 24: Linkage analysis of CDA pathophenotypes quantified in the myocardium. Lod scores after the combined therapy in old mice. The Illumina Mouse Medium Density Linkage Panel Assay was used to genotype 130 F1BX mice at 1449 single nucleotide polymorphisms (SNPs). Genotypes were classified as FVB/FVB (F/F) or FVB/C57BL/6 (F/B). Ultimately, 806 SNPs are informative from the FVB and C57BL/6 mice; the average genomic distance between these SNPs was 9.9 Mb. The genotype proportion among the F1BX mice showed a normal distribution. Linkage analysis was carried out using interval mapping with the expectation-maximization (EM) algorithm and R/QTL software. The criteria for significant and suggestive linkages for single markers were chosen based on Lander and Kruglyak (see methods section of our manuscript).-- Supplemental Dataset 25: Human breast cancer cohort-1 genotyping. The association of genetic variants with CDA was evaluated in four patient cohorts previously published by some of us. Here, 53 anthracycline-treated breast cancer patients (Breast Cancer cohort-1) [Ruiz-Pinto et al., Breast Cancer Res Treat., 2018], the cardiac function was assessed by echocardiography to evaluate the left ventricular ejection fraction (LVEF). SNVs were detected on the Infinium™ Global Screening Array-24 v2.0 BeadChip. Data were imputed using the Michigan Imputation Server with Minimac4 [Das et al., Nature Genetics 2016]; after retrieving the data, all markers with R2 < 0.7 were removed from the analysis before proceeding further. SNVs related to candidate genes identified in the mouse cohort were evaluated.-- Supplemental Dataset 26: Genes and genetic markers that were chosen to be evaluated in the breast cancer cohort-1 for the case and control assessment and also for CDA as a continuous variable. The chosen human genetic markers belong to allelic forms of candidate genes identified in the backcross mouse cohort associated with CDA risk variation.-- Supplemental Dataset 27: Human breast cancer cohort-1 and CDA evaluation through the Left Ventricular Ejection Fraction (LVEF) determined by echocardiography. LVEF values are shown before chemotherapy (LVEF-1), at first follow-up after treatment was completed (LVEF-2), and the increment of LVEF (difference between LVEF- 1 and LVEF-2). These values were used to evaluate CDA risk as a continuous variable.-- Supplemental Dataset 28: Human breast cancer cohort-2 genotyping. The association of genetic variants with CDA was evaluated in four patient cohorts previously published by some of us. Here, 420 anthracycline-treated breast cancer patients (Breast Cancer cohort-2) [Vulsteke et al., Breast Cancer Res Treat, 2015], the cardiac function was assessed by echocardiography to evaluate the left ventricular ejection fraction (LVEF). SNVs were detected on the Infinium™ Global Screening Array-24 v2.0 BeadChip. Data were imputed using the Michigan Imputation Server with Minimac4 [Das et al., Nature Genetics, 2016]; after retrieving the data, all markers with R2 < 0.7 were removed from the analysis before proceeding further. SNVs related to candidate genes identified in the mouse cohort were evaluated.-- Supplemental Dataset 29: Genes and genetic markers that were chosen to be evaluated in the breast cancer cohort-2 for the case and control assessment and also for CDA as a continuous variable. The chosen human genetic markers belong to allelic forms of candidate genes identified in the backcross mouse cohort associated with CDA risk variation.-- Supplemental Dataset 30: Human breast cancer cohort-2 and CDA evaluation through the Left Ventricular Ejection Fraction (LVEF) determined by echocardiography. LVEF values are shown before chemotherapy (LVEF-1), at first follow-up after treatment was completed (LVEF-2), and the increment of LVEF (difference between LVEF- 1 and LVEF-2). These values were used to evaluate CDA risk as a continuous variable.-- Supplemental Dataset 31: Pediatric cancer cohort genotyping. The association of genetic variants with CDA was evaluated in four patient cohorts previously published by some of us. Here, 71 anthracycline-treated pediatric cancer patients (Pediatric cohort) [Ruiz-Pinto et al., Pharmacogenetics Genomics, 2017], the cardiac function was assessed by echocardiography to evaluate the left ventricular fractional shortening (LVFS). SNVs were detected on the Infinium™ Global Screening Array-24 v2.0 BeadChip. Data were imputed using the Michigan Imputation Server with Minimac4 [Dast et al., Nature Genetics 2016]; after retrieving the data, all markers with R2 < 0.7 were removed from the analysis before proceeding further. SNVs related to candidate genes identified in the mouse cohort were evaluated.-- Supplemental Dataset 32: Genes and genetic markers that were chosen to be evaluated in the pediatric cohort for the case and control assessment and also for CDA as a continuous variable. The chosen human genetic markers belong to allelic forms of candidate genes identified in the backcross mouse cohort associated with CDA risk variation.-- Supplemental Dataset 33: Pediatric cohort and CDA evaluation through the Left Ventricular Fractional Shortening (LVFS) determined by echocardiography. LVEF values are shown before chemotherapy (LVEF-1), at first follow-up after treatment was completed (LVEF-2), and the increment of LVEF (difference between LVEF- 1 and LVEF-2). These values were used to evaluate CDA risk as a continuous variable.-- Supplemental Dataset 34: Human cancer Cardiac Magnetic Resonance (CMR) cohort genotyping. The association of genetic variants with CDA was evaluated in four patient cohorts previously published by some of us. Cardiac Magnetic Resonance (CMR) was carried out in 24 cancer patients (CMR cohort) [Barreiro-Pérez et al., Rev Esp Cardiol, 2018]. CMR was carried out at baseline and after every two cycles of a regular course of anthracycline therapy.-- Supplemental Dataset 35: Genes and genetic markers that were chosen to be evaluated in the CMR cancer cohort for the case and control assessment and also for CDA as a continuous variable. The chosen human genetic markers belong to allelic forms of candidate genes identified in the backcross mouse cohort associated with CDA risk variation., Peer reviewed

R script to generate Figure 3B in Cid, Marquez-Galera et al., (2021) (https://doi.org/10.1016/j.celrep.2021.109229)., Peer reviewed

This data table is related to the published article Cid et al., (2021), doi: https://doi.org/10.1016/j.celrep.2021.109229., Table shows results of differential expression analysis of RNA-seq data from superficial and deep sublayers of the CA1 region of the dorsal hippocampus from the brain of healthy adult rats. Superficial and deep sublayers of the CA1 region were isolated by laser capture microdissection prior to RNA isolation and library construction for RNA-seq., Peer reviewed

This data table is related to the published article Cid et al., (2021), doi: https://doi.org/10.1016/j.celrep.2021.109229., Table shows results of differential expression analysis of RNA-seq data from superficial and deep sublayers of the CA1 region of the dorsal hippocampus from the brain of epileptic adult rats. Superficial and deep sublayers of the CA1 region were isolated by laser capture microdissection prior to RNA isolation and library construction for RNA-seq., Peer reviewed

This PDF file includes: Figs. S1 to S8. Legends for tables S1 to S3. Legends for movies S1 to S3 Other Supplementary Material includes (zip): Tables S1 to S3. Movies S1 and S2, Peer reviewed

Gene expression of human chemokines and their receptors analyzed by using RT² Profiler™ PCR Array Human Chemokines & Receptors (GeneGlobe ID - PAHS-022Z, Qiagen) on a CFX Connect Real-Time PCR System (Biorad, Hercules, CA) according to manufacturer instructions., Provided is raw data expressed as Ct values corresponding to gene expression of human chemokines and their receptors analyzed by using RT² Profiler™ PCR Array Human Chemokines & Receptors (GeneGlobe ID - PAHS-022Z, Qiagen) on a CFX Connect Real-Time PCR System (Biorad, Hercules, CA). Samples: Healthy, mildly and severely inflamed tissue biopsies were collected from all patients and preserved in RNAlater. Tissue samples were obtained from 20 patients of Cronh's disease, grouped by their treatment in 4 groups (untreated, adalimumab, ustekinumab and vedolizumab). Each treatment group has 5 patients associated, with 3 samples from each patient corresponding to the tissue's relative degree of inflammation (Healthy tissue, mildly inflamed tissue, severely inflamed tissue). Clinical and analytical characteristics of patients were recorded at inclusion in the study. Disease clinical activity was determined by Crohn’s disease activity index (CDAI)>150 and presence of clinical symptoms of relapse. Disease endoscopic activity was determined by Simple Endoscopic Score for Crohn Disease (SES-CD). All patients were Caucasian of Mediterranean ethnicity and were classified according to the Montreal classification. All included patients received diaries to record symptoms 1 week before inclusion and sample collection, and signed an informed consent to participate in the study. The study was approved by the Ethics Committee of Hospital General Universitario and performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. All patients gave their informed consent prior to their inclusion in the study., Peer reviewed

The supporting information: Figure S1. Differentiating CBPf/f neurospheres infected with Cre-recombinase-encoding viruses do not express CBP. Representative images of differentiating secondary neurospheres infected with control (DsRed) or Cre-recombinase-encoding Lentiviruses stained with antibodies specific for CBP and counterstained with DAPI. Scale bars: 100 µm; Figure S2. Sensitivity analysis of snRNA-seq. Violin plots show the distribution of the number of transcripts (left, scored by UMIs) and genes (right) detected per cell for differentiating neurospheres from control (CTRL), CBPf/f (CBP), and p300f/f (P300) neurospheres. UMIs: unique molecular identifiers; Video S1. Time-lapse culture over 2 days of a control differentiating neurosphere infected with control plasmids; Video S2. Time-lapse culture over 2 days of a differentiating CBPf/f neurosphere infected with Cre plasmids; Video S3. Time-lapse culture over 2 days of a differentiating p300f/f neurosphere infected with Cre plasmids; Table S1. Gene markers for individual clusters of snRNA-seq data identified by differential expression testing using the Wilcoxon rank sum test (see methods); ; Table S2. Differential expression analysis between Crebbpf/f + Cre and control neurosphere for cluster 0 and cluster 5, using the Wilcoxon rank sum test (see methods)., Peer reviewed

Extended Data: Figure 1-1 RNA-seq samples generated in this study. Download Figure 1-1, XLSX file. Figure 1-2 Two sheets. a, Downregulated genes in the CBP-ifKO RNA-seq. b, Upregulated genes in the CBP-ifKO RNA-seq (see attached Excel file)., Figure 1: CBP, but not p300, is necessary for the normal expression of neuronal plasticity-related genes. a, Scheme presenting the genetic strategy for the generation of CBP-ifKOs and p300-ifKOs illustrated with the immunostaining of sagittal brain slices of control and ifKOs that demonstrate the loss of CBP or p300 in areas where the Camk2a-creERT2 transgene is expressed. b, IHC analysis demonstrated the loss of CBP in pyramidal and granular cells in the hippocampus of young adult (3- to 6-month-old) ifKO mice. Gene ablation is also appreciable in amygdala and cortex, but not in brain areas where the Cre recombinase is not expressed. Scale bar, 500 µm. c, WB of CBP-ifKO (green bars) and control (WT, black bars) hippocampal protein extracts confirmed the loss of CBP expression in young adult (3- to 6-month-old) CBP-ifKOs using two different antibodies against CBP. No upregulation of p300 was observed. d, RNA-seq was used for the differential expression profiling of CBP-ifKOs and control littermates (Extended Data Figs. 1-1, 1-2, additional details). Heatmap representations of upregulated and downregulated genes in young adult (3- to 6-month-old) CBP-ifKOs (top panel) and p300-ifKOs (bottom panel) referred to their respective control littermates. The creERT2 driver-related genes Esr1 and Arsi are the only genes differentially expressed in p300-ifKOs. e, GO analysis of downregulated genes in CBP-ifKOs. The top 20 GO biological process terms are shown. f, IGV profiles of two representative genes downregulated in CBP-ifKOs. g, qRT-PCR assays confirmed the downregulation of CBP target genes in the hippocampi of CBP-ifKOs. h, Comparison of DEG sets in dKAT3-ifKOs (p-adjusted < 0.05; no fold cutoff) and CBP-ifKOs. i, Overlap between the sets of genes downregulated in dKAT3-ifKOs (p-adjusted < 0.05; no cutoff) and CBP-ifKOs. j, The comparison of differential expression profiles in CBP-ifKO and Crebbp+/− mice revealed a gene dose effect and showed that many DEGs in CBP-ifKOs were also reduced in heterozygous mice, although did not reach the threshold for significance. *p-value < 0.05; **p-value < 0.01; ***p-value < 0.001., Peer reviewed

Supplementary Table 1. Characteristics of samples in Trp53-null mammary tumor cohort., Mouse models of cancer provide a powerful tool for investigating all aspects of cancer biology. In this study, we used our recently developed machine learning approach to identify the cellular morphometric biomarkers (CMB) from digital images of hematoxylin and eosin (H&E) micrographs of orthotopic Trp53-null mammary tumors (n = 154) and to discover the corresponding cellular morphometric subtypes (CMS). Of the two CMS identified, CMS-2 was significantly associated with shorter survival (p = 0.0084). We then evaluated the learned CMB and corresponding CMS model in MMTV-Erbb2 transgenic mouse mammary tumors (n = 53) in which CMS-2 was significantly correlated with the presence of metastasis (p = 0.004). We next evaluated the mouse CMB and CMS model on The Cancer Genome Atlas breast cancer (TCGA-BRCA) cohort (n = 1017). Kaplan–Meier analysis showed significantly shorter overall survival (OS) of CMS-2 patients compared to CMS-1 patients (p = 0.024) and added significant prognostic value in multi-variable analysis of clinical and molecular factors, namely, age, pathological stage, and PAM50 molecular subtype. Thus, application of CMS to digital images of routine workflow H&E preparations can provide unbiased biological stratification to inform patient care., Peer reviewed

Supplementary Table 2. Characteristics of samples in MMTV-Erbb2 mammary tumor cohort., Mouse models of cancer provide a powerful tool for investigating all aspects of cancer biology. In this study, we used our recently developed machine learning approach to identify the cellular morphometric biomarkers (CMB) from digital images of hematoxylin and eosin (H&E) micrographs of orthotopic Trp53-null mammary tumors (n = 154) and to discover the corresponding cellular morphometric subtypes (CMS). Of the two CMS identified, CMS-2 was significantly associated with shorter survival (p = 0.0084). We then evaluated the learned CMB and corresponding CMS model in MMTV-Erbb2 transgenic mouse mammary tumors (n = 53) in which CMS-2 was significantly correlated with the presence of metastasis (p = 0.004). We next evaluated the mouse CMB and CMS model on The Cancer Genome Atlas breast cancer (TCGA-BRCA) cohort (n = 1017). Kaplan–Meier analysis showed significantly shorter overall survival (OS) of CMS-2 patients compared to CMS-1 patients (p = 0.024) and added significant prognostic value in multi-variable analysis of clinical and molecular factors, namely, age, pathological stage, and PAM50 molecular subtype. Thus, application of CMS to digital images of routine workflow H&E preparations can provide unbiased biological stratification to inform patient care., Peer reviewed