Project description:A fundamental question in biology is how gene expression is regulated to give rise to a phenotype. However, transcriptional variability is rarely considered and could influence the relationship between genotype and phenotype. It is known in unicellular organisms that gene expression is often noisy rather than uniform and has been proposed to be beneficial when environmental conditions are unpredictable. However, little is known about transcriptional variability in multicellular organisms. Using transcriptomic approaches, we analysed gene expression variability over a 24 hours time-course between individual Arabidopsis thaliana plants growing in stable conditions. We identified hundreds of genes that exhibit high inter-individual variability and found that many are involved in environmental responses. We also identified factors that might facilitate gene expression variability, such as gene size, the number of transcription factors regulating a gene and the chromatin environment. These results will bring a new light into the impact of transcriptional variability in gene expression regulation in plants.
Project description:We extracted RNA from C57BL/6 mouse neutrophils to measure inter-individual variability in gene expression. 5 of the 10 blood samples were analyzed separately, the other 5 were pooled then split into 5 technical replicates to measure technical variability. We could then measure inter-individual variability in gene expression and compare it to the amplitude of miRNA-guided repression by miR-223.
Project description:A retrospective analysis of proteomics data from nine different human tissues, to understand the inter-individual and inter-tissue variability in protein expression. We used the data to build robust classifiers to predict the tissue of origin.
Project description:Diversity and individual variability are essential to human cognitive function. Identifying the conserved and variable (epi)genomic signatures of the brain’s cellular components is critical for understanding the neurobiological basis of individual variation in brain function. We applied single nucleus methylome and transcriptome sequence (snmCT-seq) to neurons from the frontal cortex of 11 adult human donors spanning a range of ages from 23 to 74, including males and females (Broadmann Area BA46). We clustered cells into brain cell types based on methylation features. We then examined the transcriptome and epigenome features in each cell type between and within individual donors. Taking advantage of the multimodal measurements in single cells, we also identified the relation between RNA expression and methylation level.These data with multiomics measurement from donors with sex and age diversity aims to approach the dimension of inter-individual variability.
Project description:Diversity and individual variability are essential to human cognitive function. Identifying the conserved and variable (epi)genomic signatures of the brain’s cellular components is critical for understanding the neurobiological basis of individual variation in brain function. We applied single nucleus methylome and transcriptome sequence (snmCT-seq) to neurons from the frontal cortex of 11 adult human donors spanning a range of ages from 23 to 74, including males and females (Broadmann Area BA46). We clustered cells into brain cell types based on methylation features. We then examined the transcriptome and epigenome features in each cell type between and within individual donors. Taking advantage of the multimodal measurements in single cells, we also identified the relation between RNA expression and methylation level.These data with multiomics measurement from donors with sex and age diversity aims to approach the dimension of inter-individual variability.
Project description:Diversity and individual variability are essential to human cognitive function. Identifying the conserved and variable (epi)genomic signatures of the brain’s cellular components is critical for understanding the neurobiological basis of individual variation in brain function. We applied single nucleus methylome and transcriptome sequence (snmCT-seq) to neurons from the frontal cortex of 11 adult human donors spanning a range of ages from 23 to 74, including males and females (Broadmann Area BA46). We clustered cells into brain cell types based on methylation features. We then examined the transcriptome and epigenome features in each cell type between and within individual donors. Taking advantage of the multimodal measurements in single cells, we also identified the relation between RNA expression and methylation level.These data with multiomics measurement from donors with sex and age diversity aims to approach the dimension of inter-individual variability.
Project description:Diversity and individual variability are essential to human cognitive function. Identifying the conserved and variable (epi)genomic signatures of the brain’s cellular components is critical for understanding the neurobiological basis of individual variation in brain function. We applied single nucleus methylome and transcriptome sequence (snmCT-seq) to neurons from the frontal cortex of 11 adult human donors spanning a range of ages from 23 to 74, including males and females (Broadmann Area BA46). We clustered cells into brain cell types based on methylation features. We then examined the transcriptome and epigenome features in each cell type between and within individual donors. Taking advantage of the multimodal measurements in single cells, we also identified the relation between RNA expression and methylation level.These data with multiomics measurement from donors with sex and age diversity aims to approach the dimension of inter-individual variability.
Project description:Diversity and individual variability are essential to human cognitive function. Identifying the conserved and variable (epi)genomic signatures of the brain’s cellular components is critical for understanding the neurobiological basis of individual variation in brain function. We applied single nucleus methylome and transcriptome sequence (snmCT-seq) to neurons from the frontal cortex of 11 adult human donors spanning a range of ages from 23 to 74, including males and females (Broadmann Area BA46). We clustered cells into brain cell types based on methylation features. We then examined the transcriptome and epigenome features in each cell type between and within individual donors. Taking advantage of the multimodal measurements in single cells, we also identified the relation between RNA expression and methylation level.These data with multiomics measurement from donors with sex and age diversity aims to approach the dimension of inter-individual variability.
Project description:Diversity and individual variability are essential to human cognitive function. Identifying the conserved and variable (epi)genomic signatures of the brain’s cellular components is critical for understanding the neurobiological basis of individual variation in brain function. We applied single nucleus methylome and transcriptome sequence (snmCT-seq) to neurons from the frontal cortex of 11 adult human donors spanning a range of ages from 23 to 74, including males and females (Broadmann Area BA46). We clustered cells into brain cell types based on methylation features. We then examined the transcriptome and epigenome features in each cell type between and within individual donors. Taking advantage of the multimodal measurements in single cells, we also identified the relation between RNA expression and methylation level.These data with multiomics measurement from donors with sex and age diversity aims to approach the dimension of inter-individual variability.
Project description:Diversity and individual variability are essential to human cognitive function. Identifying the conserved and variable (epi)genomic signatures of the brain’s cellular components is critical for understanding the neurobiological basis of individual variation in brain function. We applied single nucleus methylome and transcriptome sequence (snmCT-seq) to neurons from the frontal cortex of 11 adult human donors spanning a range of ages from 23 to 74, including males and females (Broadmann Area BA46). We clustered cells into brain cell types based on methylation features. We then examined the transcriptome and epigenome features in each cell type between and within individual donors. Taking advantage of the multimodal measurements in single cells, we also identified the relation between RNA expression and methylation level.These data with multiomics measurement from donors with sex and age diversity aims to approach the dimension of inter-individual variability.