Browse
Submit Data
Databases
API
Help

Dataset Information

14 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Assessing the relevance of organoids to model inter-individual variation

ABSTRACT: The purpose of this project is to assess the relevance of pluripotent stem cell-derived cerebral and liver organoids to recapitulate the variation in cell-type specific gene expression programs between individuals. Towards this aim, we will generate reference atlases of the developing cortex and liver from multiple individuals, derive iPSC lines from these same individuals, and determine if inter-individual gene expression variation is recapitulated in cerebral and liver organoids from the same individual from which we have reference maps. In parallel we will assess the genetic contribution to variablity between organoids from different iPSCs of multiple human individuals that are available in existing iPSC resources (e.g. HipSci).

SUBMITTER: Barbara Treutlein

PROVIDER: S-SUBS2 | biostudies-other |

SECONDARY ACCESSION(S): SAMEA5643396

REPOSITORIES: biostudies-other

ACCESS DATA

Json Xml

Similar Datasets

C. elegans as a model for inter-individual variation in metabolism

Project description:Fox BW, Ponomarova O, Lee YU, Zhang G, Giese EG, Walker M, Roberto NM, Na H, Reis-Rodrigues P, Curtis BJ, Kolodziej AR, Crombie TA, Zdraljevic S, Yilmaz LS, Andersen EC, Schroeder FC, Walhout AJM (2022) C. elegans as a model for inter-individual variation in metabolism

2021-07-13 | MSV000087810 | MassIVE

Human milk dynamics: Inter-individual variation in peptidome

Project description:The aim of this study was to map inter-individual variation in the human milk peptidome and to investigate relationships between these data and possible explanations for observed variation.

2022-05-04 | PXD028294 | Pride

Human milk dynamics: Inter-individual variation in milk proteome

Project description:The aim of this study was to map inter-individual variation in the human milk proteome and to investigate relationships between these data and possible explanations for observed variation.

2022-05-04 | PXD028280 | Pride

Inter-individual variation among worms in a shared environment

Project description:Isogenic individuals growing in the same environment often show substantial phenotypic variation. The causes, consequences and molecular bases of inter-individual variation are usually poorly understood. To characterize molecular differences between isogenic individuals, we measured genome-wide expression profiles in synchronized single young adult C. elegans worms.

2017-12-05 | GSE98747 | GEO

Assessing inter- and intra-individual DNA methylation profiles in human brain samples

Project description:We report the application of single molecule-based sequencing technology in combination with MBD affinity purifcation (MAP-seq) to generate methylation maps in a panel of human brain samples. Here we assay the methylation status of the human genome in eight distinct brain regions from three individuals in addition to a further thirty six hippocampal samples. The cerebellum was a consistent outlier compared to all other regions, showing over 16,000 differentially methylated regions (DMRs). Unexpectedly, the sequence properties of hypo- and hyper- methylated domains in cerebellum were distinct. In contrast we found very few DMRs that could distinguish between regions of the cortex, limbic system and brain stem. Inter-individual DMRs were readily detectable, however with the exception of cerebellum, DNA methylation patterns are more similar between different brain regions from the same individual, than they are for a single brain region between different individuals.

2014-12-01 | GSE50960 | GEO

Inter-individual variation in morphine clearance in children.

Project description:ObjectivesThe aim of the study was to determine the extent of inter-individual variation in clearance of intravenous morphine in children and to establish which factors are responsible for this variation.MethodsA systematic literature review was performed to identify papers describing the clearance of morphine in children. The following databases were searched: Medline, Embase, International Pharmaceutical Abstracts, CINAHL, and Cochrane library. From the papers, the range in plasma clearance and the coefficient of variation (CV) in plasma clearance were determined.ResultsTwenty-eight studies were identified. After quality assessment, 20 studies were included. Only 10 studies gave clearance values for individual patients. The majority of the studies were in critically ill patients. Inter-individual variability of morphine clearance was observed in all age groups, but greatest in critically ill neonates (both preterm and term) and infants. In critically ill patients, the CV was 16-97% in preterm neonates, 24-87% in term neonates, 35 and 134% in infants, 39 and 55% in children, and 74% in adolescents. The CV was 37 and 44% respectively in non-critically ill neonates and infants. The mean clearance was higher in children (32 and 52 ml min(-1) kg(-1)) than in neonates (2 to 16 ml min(-1) kg(-1)).ConclusionsLarge inter-individual variation was seen in morphine clearance values in critically ill neonates and infants.

| S-EPMC4430598 | biostudies-literature

GNPS - C. elegans as a model for inter-individual variation in metabolism

2021-07-13 | MSV000087810 | GNPS

Evaluating intra- and inter-individual variation in the human placental transcriptome

Project description:Background: Gene expression variation is a phenotypic trait of particular interest as it represents the initial link between genotype and other phenotypes. Analyzing how such variation apportions among and within groups allows for the evaluation of how genetic and environmental factors influence such traits. It also provides opportunities to identify genes and pathways that may have been influenced by non-neutral processes. Here we use a population genetics framework and next generation sequencing to evaluate how gene expression variation is apportioned among four human groups in a natural biological tissue, the placenta. Results: We estimate that on average, 33.2%, 58.9% and 7.8% of the placental transcriptome is explained by variation within individuals, among individuals and among human groups, respectively. Additionally, when technical and biological traits are included in models of gene expression they account for roughly 2% of total gene expression variation. Notably, the variation that is significantly different among groups is enriched in biological pathways associated with immune response, cell signaling and metabolism. Many biological traits demonstrated correlated changes in expression in numerous pathways of potential interest to clinicians and evolutionary biologists. Finally, we estimate that the majority of the human placental transcriptome (65% of expressed genes) exhibits expression profiles consistent with neutrality; the remainder are consistent with stabilizing selection (26%), directional selection (4.9%), or diversifying selection (4.8%). Conclusion: We apportion placental gene expression variation into individual, population and biological trait factors and identify how each influence the transcriptome. Additionally, we advance methods to associate expression profiles with different forms of selection.

2015-03-07 | GSE66622 | GEO

Drivers of Inter-individual Variation in Dengue Viral Load Dynamics.

Project description:Dengue is a vector-borne viral disease of humans that endemically circulates in many tropical and subtropical regions worldwide. Infection with dengue can result in a range of disease outcomes. A considerable amount of research has sought to improve our understanding of this variation in disease outcomes and to identify predictors of severe disease. Contributing to this research, patterns of viral load in dengue infected patients have been quantified, with analyses indicating that peak viral load levels, rates of viral load decline, and time to peak viremia are useful predictors of severe disease. Here, we take a complementary approach to understanding patterns of clinical manifestation and inter-individual variation in viral load dynamics. Specifically, we statistically fit mathematical within-host models of dengue to individual-level viral load data to test virological and immunological hypotheses explaining inter-individual variation in dengue viral load. We choose between alternative models using model selection criteria to determine which hypotheses are best supported by the data. We first show that the cellular immune response plays an important role in regulating viral load in secondary dengue infections. We then provide statistical support for the process of antibody-dependent enhancement (but not original antigenic sin) in the development of severe disease in secondary dengue infections. Finally, we show statistical support for serotype-specific differences in viral infectivity rates, with infectivity rates of dengue serotypes 2 and 3 exceeding those of serotype 1. These results contribute to our understanding of dengue viral load patterns and their relationship to the development of severe dengue disease. They further have implications for understanding how dengue transmissibility may depend on the immune status of infected individuals and the identity of the infecting serotype.

| S-EPMC5113863 | biostudies-literature

Basic Units of Inter-Individual Variation in Resting State Connectomes.

Project description:Resting state functional connectomes are massive and complex. It is an open question, however, whether connectomes differ across individuals in a correspondingly massive number of ways, or whether most differences take a small number of characteristic forms. We systematically investigated this question and found clear evidence of low-rank structure in which a modest number of connectomic components, around 50-150, account for a sizable portion of inter-individual connectomic variation. This number was convergently arrived at with multiple methods including estimation of intrinsic dimensionality and assessment of reconstruction of out-of-sample data. In addition, we show that these connectomic components enable prediction of a broad array of neurocognitive and clinical symptom variables at levels comparable to a leading method that is trained on the whole connectome. Qualitative observation reveals that these connectomic components exhibit extensive community structure reflecting interrelationships between intrinsic connectivity networks. We provide quantitative validation of this observation using novel stochastic block model-based methods. We propose that these connectivity components form an effective basis set for quantifying and interpreting inter-individual connectomic differences, and for predicting behavioral/clinical phenotypes.

| S-EPMC6374507 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data