28 Works

Additional file 3 of Genetically predicted telomere length and Alzheimer’s disease endophenotypes: a Mendelian randomization study

Blanca Rodríguez-Fernández, Natalia Vilor-Tejedor, Eider M. Arenaza-Urquijo, Gonzalo Sánchez-Benavides, Marc Suárez-Calvet, Grégory Operto, Carolina Minguillón, Karine Fauria, Gwendlyn Kollmorgen, Ivonne Suridjan, Manuel Castro de Moura, David Piñeyro, Manel Esteller, Kaj Blennow, Henrik Zetterberg, Immaculata De Vivo, José Luis Molinuevo, Arcadi Navarro, Juan Domingo Gispert, Aleix Sala-Vila & Marta Crous-Bou
Additional file 3: Supplementary Table 1. Characteristics of the study participants with information for cognition outcomes. Mean and SD are shown for continuous variables. Supplementary Table 2. Characteristics of the study participants with information for neuroimaging outcomes. Mean and SD are shown for continuous variables. Supplementary Table 3. Characteristics of the study participants with information for CSF biomarkers. Mean and SD are shown for continuous variables.

Additional file 5 of Genetically predicted telomere length and Alzheimer’s disease endophenotypes: a Mendelian randomization study

Blanca Rodríguez-Fernández, Natalia Vilor-Tejedor, Eider M. Arenaza-Urquijo, Gonzalo Sánchez-Benavides, Marc Suárez-Calvet, Grégory Operto, Carolina Minguillón, Karine Fauria, Gwendlyn Kollmorgen, Ivonne Suridjan, Manuel Castro de Moura, David Piñeyro, Manel Esteller, Kaj Blennow, Henrik Zetterberg, Immaculata De Vivo, José Luis Molinuevo, Arcadi Navarro, Juan Domingo Gispert, Aleix Sala-Vila & Marta Crous-Bou
Additional file 5: Supplementary Figure 1. Leave-one-out permutation analysis plot for AD signature among individuals at high genetic predisposition to AD obtained by leaving out the SNP indicated and repeating the Inverse-Variance Weighted method with the rest of the instrumental variables. Supplementary Figure 2. Leave-one-out permutation analysis plot for Aging signature among individuals at high genetic predisposition to AD, obtained by leaving out the SNP indicated and repeating the Inverse-Variance Weighted method with the rest...

Additional file 5 of scTAM-seq enables targeted high-confidence analysis of DNA methylation in single cells

Agostina Bianchi, Michael Scherer, Roser Zaurin, Kimberly Quililan, Lars Velten & Renée Beekman
Additional file 5: Table S4. Non-HhaI amplicons used for cell selection.

Additional file 2 of scTAM-seq enables targeted high-confidence analysis of DNA methylation in single cells

Agostina Bianchi, Michael Scherer, Roser Zaurin, Kimberly Quililan, Lars Velten & Renée Beekman
Additional file 2: Table S1. Design overview of the panel of targeted regions.

Additional file 4 of scTAM-seq enables targeted high-confidence analysis of DNA methylation in single cells

Agostina Bianchi, Michael Scherer, Roser Zaurin, Kimberly Quililan, Lars Velten & Renée Beekman
Additional file 4: Table S3. Complete list of CpG methylation-sensitive endonucleases potentially compatible with scTAM-seq.

Additional file 7 of scTAM-seq enables targeted high-confidence analysis of DNA methylation in single cells

Agostina Bianchi, Michael Scherer, Roser Zaurin, Kimberly Quililan, Lars Velten & Renée Beekman
Additional file 7: Table S6. Doublet detection details per sample and condition.

Additional file 1 of Parallel evolution of amphioxus and vertebrate small-scale gene duplications

Marina Brasó-Vives, Ferdinand Marlétaz, Amina Echchiki, Federica Mantica, Rafael D. Acemel, José L. Gómez-Skarmeta, Diego A. Hartasánchez, Lorlane Le Targa, Pierre Pontarotti, Juan J. Tena, Ignacio Maeso, Hector Escriva, Manuel Irimia & Marc Robinson-Rechavi
Additional file 1: Table S1-Table S6.

Additional file 1 of Parallel evolution of amphioxus and vertebrate small-scale gene duplications

Marina Brasó-Vives, Ferdinand Marlétaz, Amina Echchiki, Federica Mantica, Rafael D. Acemel, José L. Gómez-Skarmeta, Diego A. Hartasánchez, Lorlane Le Targa, Pierre Pontarotti, Juan J. Tena, Ignacio Maeso, Hector Escriva, Manuel Irimia & Marc Robinson-Rechavi
Additional file 1: Table S1-Table S6.

Additional file 3 of Genetically predicted telomere length and Alzheimer’s disease endophenotypes: a Mendelian randomization study

Blanca Rodríguez-Fernández, Natalia Vilor-Tejedor, Eider M. Arenaza-Urquijo, Gonzalo Sánchez-Benavides, Marc Suárez-Calvet, Grégory Operto, Carolina Minguillón, Karine Fauria, Gwendlyn Kollmorgen, Ivonne Suridjan, Manuel Castro de Moura, David Piñeyro, Manel Esteller, Kaj Blennow, Henrik Zetterberg, Immaculata De Vivo, José Luis Molinuevo, Arcadi Navarro, Juan Domingo Gispert, Aleix Sala-Vila & Marta Crous-Bou
Additional file 3: Supplementary Table 1. Characteristics of the study participants with information for cognition outcomes. Mean and SD are shown for continuous variables. Supplementary Table 2. Characteristics of the study participants with information for neuroimaging outcomes. Mean and SD are shown for continuous variables. Supplementary Table 3. Characteristics of the study participants with information for CSF biomarkers. Mean and SD are shown for continuous variables.

Data for \"Eighty million years of rapid evolution of the primate Y chromosomes\"

Yang Zhou, Xiaoyu Zhan, Jiazheng Jin, Long Zhou, Juraj Bergman, Xuemei Li, Marjolaine Marie C Rousselle, Meritxell Riera Belles, Lan Zhao, Miaoquan Fang, Qi Fang, Lukas Kuderna, Tomas Marques-Bonet, Haruka Kitayama, Takashi Hayakawa, Yong-Gang Yao, Huanming Yang, David N. Cooper, Xiaoguang Qi, Dong-Dong Wu, Mikkel Heide Schierup & Guojie Zhang
This folder contains data for "Eighty million years of rapid evolution of the primate Y chromosome" gene_set.zip contains gene annotation (GFF, CDS, PEP, POS.ADD) for the 30 species used in this study XY_location.zip contains the genomic coordinates for PAR, nonPARX and nonPARY (BED format). Species names are in the 4th column. gametolog_alignment.tar.gz contains gametolog alignment (PHY format) used to calculate pairwise dN/dS. S5.tree.zip contains alignment (FASTA format) and constructed phylogeny (NWK format) for each S5...

Additional file 4 of scTAM-seq enables targeted high-confidence analysis of DNA methylation in single cells

Agostina Bianchi, Michael Scherer, Roser Zaurin, Kimberly Quililan, Lars Velten & Renée Beekman
Additional file 4: Table S3. Complete list of CpG methylation-sensitive endonucleases potentially compatible with scTAM-seq.

Additional file 7 of scTAM-seq enables targeted high-confidence analysis of DNA methylation in single cells

Agostina Bianchi, Michael Scherer, Roser Zaurin, Kimberly Quililan, Lars Velten & Renée Beekman
Additional file 7: Table S6. Doublet detection details per sample and condition.

Additional file 8 of scTAM-seq enables targeted high-confidence analysis of DNA methylation in single cells

Agostina Bianchi, Michael Scherer, Roser Zaurin, Kimberly Quililan, Lars Velten & Renée Beekman
Additional file 8: Table S7 and Table S8. Correlation analysis between target CpGs and gene expression.

Additional file 1 of Genetically predicted telomere length and Alzheimer’s disease endophenotypes: a Mendelian randomization study

Blanca Rodríguez-Fernández, Natalia Vilor-Tejedor, Eider M. Arenaza-Urquijo, Gonzalo Sánchez-Benavides, Marc Suárez-Calvet, Grégory Operto, Carolina Minguillón, Karine Fauria, Gwendlyn Kollmorgen, Ivonne Suridjan, Manuel Castro de Moura, David Piñeyro, Manel Esteller, Kaj Blennow, Henrik Zetterberg, Immaculata De Vivo, José Luis Molinuevo, Arcadi Navarro, Juan Domingo Gispert, Aleix Sala-Vila & Marta Crous-Bou
Additional file 1: Supplementary Table 1. Characteristics of Single Nucleotide Polymorphisms (SNPs) associated with longer telomere length. The effect allele refers to the allele that is associated with longer telomere length. Chromosomal position of the SNPs (genome assembly GRCh37 (hg19)) according to the public archive for genetic variation within and across different species developed and hosted by the National Center for Biotechnology Information (NCBI) in collaboration with the National Human Genome Research Institute (NHGRI) (dbSNP).

Additional file 4 of Genetically predicted telomere length and Alzheimer’s disease endophenotypes: a Mendelian randomization study

Blanca Rodríguez-Fernández, Natalia Vilor-Tejedor, Eider M. Arenaza-Urquijo, Gonzalo Sánchez-Benavides, Marc Suárez-Calvet, Grégory Operto, Carolina Minguillón, Karine Fauria, Gwendlyn Kollmorgen, Ivonne Suridjan, Manuel Castro de Moura, David Piñeyro, Manel Esteller, Kaj Blennow, Henrik Zetterberg, Immaculata De Vivo, José Luis Molinuevo, Arcadi Navarro, Juan Domingo Gispert, Aleix Sala-Vila & Marta Crous-Bou
Additional file 4: Supplementary Table 1. Results of the effect of genetically predicted longer telomere length on AD endophenotypes in the entire sample. Supplementary Table 2. Results of the effect of genetically predicted longer telomere length on AD endophenotypes among APOE-ɛ4 carriers. Supplementary Table 3. Results of the effect of genetically predicted longer telomere length on AD endophenotypes among APOE-ɛ4 non-carriers. Supplementary Table 4. Results of the effect of genetically predicted longer telomere length on...

Additional file 5 of Genetically predicted telomere length and Alzheimer’s disease endophenotypes: a Mendelian randomization study

Blanca Rodríguez-Fernández, Natalia Vilor-Tejedor, Eider M. Arenaza-Urquijo, Gonzalo Sánchez-Benavides, Marc Suárez-Calvet, Grégory Operto, Carolina Minguillón, Karine Fauria, Gwendlyn Kollmorgen, Ivonne Suridjan, Manuel Castro de Moura, David Piñeyro, Manel Esteller, Kaj Blennow, Henrik Zetterberg, Immaculata De Vivo, José Luis Molinuevo, Arcadi Navarro, Juan Domingo Gispert, Aleix Sala-Vila & Marta Crous-Bou
Additional file 5: Supplementary Figure 1. Leave-one-out permutation analysis plot for AD signature among individuals at high genetic predisposition to AD obtained by leaving out the SNP indicated and repeating the Inverse-Variance Weighted method with the rest of the instrumental variables. Supplementary Figure 2. Leave-one-out permutation analysis plot for Aging signature among individuals at high genetic predisposition to AD, obtained by leaving out the SNP indicated and repeating the Inverse-Variance Weighted method with the rest...

Additional file 3 of scTAM-seq enables targeted high-confidence analysis of DNA methylation in single cells

Agostina Bianchi, Michael Scherer, Roser Zaurin, Kimberly Quililan, Lars Velten & Renée Beekman
Additional file 3: Table S2. Sequencing details per sample and condition.

Additional file 6 of scTAM-seq enables targeted high-confidence analysis of DNA methylation in single cells

Agostina Bianchi, Michael Scherer, Roser Zaurin, Kimberly Quililan, Lars Velten & Renée Beekman
Additional file 6: Table S5. PCR program for DNA digestion and targeted amplification steps.

Additional file 6 of scTAM-seq enables targeted high-confidence analysis of DNA methylation in single cells

Agostina Bianchi, Michael Scherer, Roser Zaurin, Kimberly Quililan, Lars Velten & Renée Beekman
Additional file 6: Table S5. PCR program for DNA digestion and targeted amplification steps.

Additional file 3 of scTAM-seq enables targeted high-confidence analysis of DNA methylation in single cells

Agostina Bianchi, Michael Scherer, Roser Zaurin, Kimberly Quililan, Lars Velten & Renée Beekman
Additional file 3: Table S2. Sequencing details per sample and condition.

Additional file 5 of scTAM-seq enables targeted high-confidence analysis of DNA methylation in single cells

Agostina Bianchi, Michael Scherer, Roser Zaurin, Kimberly Quililan, Lars Velten & Renée Beekman
Additional file 5: Table S4. Non-HhaI amplicons used for cell selection.

Additional file 8 of scTAM-seq enables targeted high-confidence analysis of DNA methylation in single cells

Agostina Bianchi, Michael Scherer, Roser Zaurin, Kimberly Quililan, Lars Velten & Renée Beekman
Additional file 8: Table S7 and Table S8. Correlation analysis between target CpGs and gene expression.

Additional file 2 of scTAM-seq enables targeted high-confidence analysis of DNA methylation in single cells

Agostina Bianchi, Michael Scherer, Roser Zaurin, Kimberly Quililan, Lars Velten & Renée Beekman
Additional file 2: Table S1. Design overview of the panel of targeted regions.

Additional file 1 of Genetically predicted telomere length and Alzheimer’s disease endophenotypes: a Mendelian randomization study

Blanca Rodríguez-Fernández, Natalia Vilor-Tejedor, Eider M. Arenaza-Urquijo, Gonzalo Sánchez-Benavides, Marc Suárez-Calvet, Grégory Operto, Carolina Minguillón, Karine Fauria, Gwendlyn Kollmorgen, Ivonne Suridjan, Manuel Castro de Moura, David Piñeyro, Manel Esteller, Kaj Blennow, Henrik Zetterberg, Immaculata De Vivo, José Luis Molinuevo, Arcadi Navarro, Juan Domingo Gispert, Aleix Sala-Vila & Marta Crous-Bou
Additional file 1: Supplementary Table 1. Characteristics of Single Nucleotide Polymorphisms (SNPs) associated with longer telomere length. The effect allele refers to the allele that is associated with longer telomere length. Chromosomal position of the SNPs (genome assembly GRCh37 (hg19)) according to the public archive for genetic variation within and across different species developed and hosted by the National Center for Biotechnology Information (NCBI) in collaboration with the National Human Genome Research Institute (NHGRI) (dbSNP).

Additional file 2 of Genetically predicted telomere length and Alzheimer’s disease endophenotypes: a Mendelian randomization study

Blanca Rodríguez-Fernández, Natalia Vilor-Tejedor, Eider M. Arenaza-Urquijo, Gonzalo Sánchez-Benavides, Marc Suárez-Calvet, Grégory Operto, Carolina Minguillón, Karine Fauria, Gwendlyn Kollmorgen, Ivonne Suridjan, Manuel Castro de Moura, David Piñeyro, Manel Esteller, Kaj Blennow, Henrik Zetterberg, Immaculata De Vivo, José Luis Molinuevo, Arcadi Navarro, Juan Domingo Gispert, Aleix Sala-Vila & Marta Crous-Bou
Additional file 2: Supplementary Table 1. Linear regression estimates for cognition outcomes in the entire sample. All models are adjusted for covariates: age, sex, education, and APOE status. Supplementary Table 2. Linear regression estimates for neuroimaging outcomes (i.e., Alzheimer’s disease and aging signatures) outcome in the entire sample. All models are adjusted for covariates: age, sex, education, and APOE status. Supplementary Table 3. Linear regression estimates for CSF biomarkers outcomes in the entire sample. All...

Registration Year

  • 2022
    28

Resource Types

  • Dataset
    28

Affiliations

  • Centre for Genomic Regulation
    28
  • Barcelona Institute for Science and Technology
    26
  • Pompeu Fabra University
    26
  • August Pi i Sunyer Biomedical Research Institute
    24
  • Institució Catalana de Recerca i Estudis Avançats
    14
  • Saarland University
    13
  • Max Planck Institute for Informatics
    13
  • Centro Nacional de Análisis Genómico
    13
  • University of Barcelona
    12
  • University College London
    12