Biology subjects

Seaton, D. D.

Publications and source records attributed to Seaton, D. D..

9 recordsLinked to original sources

bioRxiv2024

Genetic instrumental variable framework for assessing relevance of in-vitro cellular phenotypes to organism-level phenotypes

Gene perturbation screens (e.g. CRISPR-Cas9) assess the impact of gene disruption on in-vitro cellular phenotypes (e.g., proliferation, anti-viral response, transcriptomics). In-vitro experiments can be useful models for understanding the aetiology of in-vivo (organismal) phenotypes. For example, anti-viral response in immune cells and infectious disease outcomes. However, assessing whether an in-vitro cellular model is effectively capturing in-vivo biology is challenging. An in-vitro model is transportable to an in-vivo phenotype of interest if perturbations impacting the in-vitro phenotype also impact the in-vivo phenotype with mechanism-consistent directionality and effect sizes. We propose a framework; Gene Perturbation Analysis for Transportability (GPAT), to assess model transportability using gene perturbation effect estimates from perturbation screens (in-vitro cellular phenotypes) and loss-of-function burden tests (in-vivo phenotypes). Using UK Biobank whole-genome sequence data and data from published genome-wide CRISPR-Cas9 screens, we evaluated transportability of in-vitro cellular models to in-vivo human phenotypes. In hypothesis-driven analyses, we found evidence that higher lysosomal cholesterol accumulation in-vitro is a transportable model for lower LDL-cholesterol measured in human blood plasma (P = 0.0006), consistent with the known role of lysosomes in lipid biosynthesis. In contrast, we found limited evidence for other putative in-vitro models. In hypothesis-free analyses, we found strong evidence for transportability of proliferation in cancer cell lines for in-vivo human plasma cellular phenotypes. For example, higher proliferation in an erythroleukemia cell line and lower plasma lymphocyte percentage. GPAT enables systematic evaluation of the transportability of in-vitro cellular models to in-vivo phenotypes, informing assay prioritization and supporting novel hypothesis generation.

genetics↗

bioRxiv2020

Population-scale single-cell RNA-seq profiling across dopaminergic neuron differentiation

Common genetic variants can have profound effects on cellular function, but studying these effects in primary human tissue samples and during development is challenging. Human induced pluripotent stem cell (iPSC) technology holds great promise for assessing these effects across different differentiation contexts. Here, we use an efficient pooling strategy to differentiate 215 iPS cell lines towards a midbrain neural fate, including dopaminergic neurons, and profile over 1 million cells sampled across three differentiation timepoints using single cell RNA sequencing. We find that the proportion of neuronal cells produced by each cell line is highly reproducible over different experimental batches, and identify robust molecular markers in pluripotent cells that predict line-to-line differences in cell fate. We identify expression quantitative trait loci (eQTL) that manifest at different stages of neuronal development, and in response to oxidative stress, by exposing cells to rotenone. We find over one thousand eQTL that colocalise with a known risk locus for a neurological trait, nearly half of which are not found in GTEx. Our study illustrates how coupling single cell transcriptomics with long-term iPSC differentiation can profile mechanistic effects of human trait-associated genetic variants in otherwise inaccessible cell states.

genetics↗

bioRxiv2020

Erosion of human X chromosome inactivation alters proteome expression from genes across the X chromosome and all autosomes

X chromosome inactivation (XCI) is a dosage compensation mechanism in female mammals whereby genes from one X chromosome are repressed. Analysis of human induced pluripotent stem cell (iPSC) lines using proteomics, RNAseq and polysome profiling showed a major change in the proteome upon XCI erosion. This resulted in amplified RNA and protein expression from X-linked genes. However, increased protein expression was also detected from autosomal genes without a corresponding mRNA increase, altering the protein-RNA correlation between genes on the X chromosome and autosomes. Eroded iPSC lines display ~13% increase in cell protein content, along with increased expression of ribosomal proteins, ribosome biogenesis and translation factors. They also showed significantly increased levels of active polysomes within the eroded lines. We conclude that erosion of XCI causes a major remodelling of the proteome, with translational mechanisms affecting the expression of a much wider range of proteins and disease-linked loci than previously realised.

biochemistry↗

bioRxiv2019

Systematic assessment of regulatory effects of human disease variants in pluripotent cells

Identifying regulatory genetic effects in pluripotent cells provides important insights into disease variants with potentially transient or developmental origins. Combining existing and newly-generated data, we characterized 1,367 iPSC lines from 948 unique donors, collectively analyzed within the \"Integrated iPSC QTL\" (i2QTL) Consortium. The sample size of our study allowed us to derive the most comprehensive map of quantitative trait loci (QTL) in pluripotent human cells to date. We mapped the effects of nearby common genetic variants on five expression phenotypes, identifying cis-QTL at gene-, exon-level and transcript-, splicing-, alternative polyadenylation-ratio (APA) for a total of 18,556 genes. For gene-level, we further quantified the effects of rare and singleton variants, and the effect of distal variants that act in trans (trans-eQTL), which we replicated in independent samples. Our data are a valuable community resource, uncovering novel regulatory effects that have not previously been described in differentiated cells and tissues. Building on this regulatory map, we functionally explore GWAS signals for over 4,336 trait loci, finding evidence for colocalization with common and rare iPSC QTL for traits such as height and BMI, and diseases, such as cancer and coronary artery disease.

genomics↗

bioRxiv2019

Single-cell RNA-seq of differentiating iPS cells reveals dynamic genetic effects on gene expression

Recent developments in stem cell biology have enabled the study of cell fate decisions in early human development that are impossible to study in vivo. However, understanding how development varies across individuals and, in particular, the influence of common genetic variants during this process has not been characterised. Here, we exploit human iPS cell lines from 125 donors, a pooled experimental design, and single-cell RNA-sequencing to study population variation of endoderm differentiation. We identify molecular markers that are predictive of differentiation efficiency, and utilise heterogeneity in the genetic background across individuals to map hundreds of expression quantitative trait loci that influence expression dynamically during differentiation and across cellular contexts.

genomics↗

bioRxiv2018

Population-scale proteome variation in human induced pluripotent stem cells

Realising the potential of human induced pluripotent stem cell (iPSC) technology for drug discovery, disease modelling and cell therapy requires an understanding of variability across iPSC lines. While previous studies have characterized iPS cell lines genetically and transcriptionally, little is known about the variability of the iPSC proteome. Here, we present the first comprehensive proteomic iPSC dataset, analysing 202 iPSC lines derived from 151 donors. We characterise the major genetic determinants affecting proteome and transcriptome variation across iPSC lines and identify key regulatory mechanisms affecting variation in protein abundance. Our data identified >700 human iPSC protein quantitative trait loci (pQTLs). We mapped trans regulatory effects, identifying an important role for protein-protein interactions. We discovered that pQTLs show increased enrichment in disease-linked GWAS variants, compared with RNA-based eQTLs.

genomics↗

bioRxiv2018

Circadian protein regulation in the green lineage I. A phospho-dawn anticipates light onset before proteins peak in daytime.

Diel regulation of protein levels and protein modification had been less studied than transcript rhythms. Here, we compare transcriptome data under light-dark cycles to partial proteome and phosphoproteome data, assayed using shotgun mass-spectrometry, from the alga Ostreococcus tauri, the smallest free-living eukaryote. 10% of quantified proteins but two-thirds of phosphoproteins were rhythmic. Mathematical modelling showed that light-stimulated protein synthesis can account for the observed clustering of protein peaks in the daytime. Prompted by night-peaking and apparently dark-stable proteins, we also tested cultures under prolonged darkness, where the proteome changed less than under the diel cycle. The dark-stable, prasinophyte-specific proteins were also reported to accumulate when O. tauri formed lipid droplets. In the phosphoproteome, 39% of rhythmic phospho-sites reached peak levels just before dawn. This anticipatory phosphorylation suggests that a clock-regulated phospho-dawn prepares green cells for daytime functions. Acid-directed and proline-directed protein phosphorylation sites were regulated in antiphase, implicating the clock-related, casein kinases 1 and 2 in phase-specific regulation, alternating with the CMGC protein kinase family. Understanding the dynamic phosphoprotein network should be facilitated by the minimal kinome and proteome of O. tauri. The data are available from ProteomeXchange, with identifiers PXD001734, PXD001735 and PXD002909. This submission updates a previous version, posted on bioRxiv on 4th April 2018, as https://www.biorxiv.org/content/10.1101/287862v1 HighlightThe phosphorylation of most protein sites was rhythmic under light-dark cycles, and suggested circadian control by particular kinases. Day-peaking, rhythmic proteins likely reflect light-stimulated protein synthesis in this microalga.

plant biology↗

bioRxiv2018

Mechanistic model of temperature influence on flowering through whole-plant accumulation of FT

We assessed temperature influence on flowering by incorporating temperature-responsive flowering mechanisms across developmental age into an existing model. Temperature influences both the leaf production rate and expression of FLOWERING LOCUS T (FT), a photoperiodic flowering regulator, in leaves. The Arabidopsis Framework Model incorporated temperature influence on leaf growth but ignored the consequences of leaf growth on and direct temperature influence of FT expression. We measured FT production in differently aged leaves and modified the model, adding the mechanistic temperature influence on FT transcription, and linking FT to leaf growth. Our simulations suggest that in long days, the developmental timing (leaf number) at which the reproductive transition occurs is influenced by day length and temperature through FT, while temperature influences the rate of leaf production and the time (in days) the transition occurs. Further, we demonstrated that FT is mainly produced in the first 10 leaves in the Columbia ecotype, and that FT accumulation alone cannot explain flowering in conditions in which flowering is delayed. Our simulations supported our hypotheses that: 1) temperature regulation of FT, accumulated with leaf growth, is a component of thermal time, and 2) incorporating mechanistic temperature regulation of FT can improve model predictions in fluctuating temperatures.

plant biology↗

bioRxiv2017

Linking circadian time to growth rate quantitatively via carbon metabolism

Predicting a multicellular organisms phenotype quantitatively from its genotype is challenging, as genetic effects must propagate across scales. Circadian clocks are intracellular regulators that control temporal gene expression patterns and hence metabolism, physiology and behaviour. Here we explain and predict canonical phenotypes of circadian timing in a multicellular, model organism. We used diverse metabolic and physiological data to combine and extend mathematical models of rhythmic gene expression, photoperiod-dependent flowering, elongation growth and starch metabolism within a Framework Model for the vegetative growth of Arabidopsis thaliana, sharing the model and data files in a structured, public resource. The calibrated model predicted the effect of altered circadian timing upon each particular phenotype in clock-mutant plants under standard laboratory conditions. Altered night-time metabolism of stored starch accounted for most of the decrease in whole-plant biomass, as previously proposed. Mobilisation of a secondary store of malate and fumarate was also mis-regulated, accounting for any remaining biomass defect. We test three candidate mechanisms for the accumulation of these organic acids. Our results link genotype through specific processes to higher-level phenotypes, formalising our understanding of a subtle, pleiotropic syndrome at the whole-organism level, and validating the systems approach to understand complex traits starting from intracellular circuits. This work updates the first biorXiv version, February 2017, https://doi.org/10.1101/105437, with an expanded description and additional analysis of the same core data sets and the same FMv2 model, summary tables and supporting, follow-on data from three further studies with further collaborators. This biorXiv revision constitutes the second version of this report.

systems biology↗