Grant de Jong

Grant de Jong

Computational biologist

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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

Pages

Posts

portfolio

publications

A survey of ancient paralog expression patterns in Arabidopsis thaliana root cell-types

Published in TBD, 2020

While the extent to which AS influences functional or regulatory divergence in ancient paralogs has been previously investigated, such as those derived from the α-WGD event in Arabidopsis thaliana, the manifestation of this divergence in distinct tissues and cell-types is less understood. Using RNA-Seq data I have surveyed the transcriptomes of root developmental zones and their constituent cell-types in paleopolyploid Arabidopsis thaliana. Incorporating such high-resolution data with further in silico analyses, this demonstrates near-complete divergence in both gene expression and splicing patterns.

Recommended citation: TBD TBD

Analysis of multiple Brassica transcriptomes reveals subgenome dominance in the response of Brassica napus to Sclerotinia sclerotiorum

Published in The Plant Journal, 2023

Allopolyploids are organisms which form due to the hybridization between two re- lated parental species, resulting in a whole-genome duplication. This phenomenon is particularly common among agronomically relevant plant species, partly due to the adaptive potential conferred through an influx of genetic material, and corre- spondingly, enhanced genetic diversity. However, these species must reconcile di- vergent parental transcriptomes, which can have profound consequences on global gene expression patterns — especially when confronted with environmental stres- sors. I used RNA-sequencing to investigate not only the response of Brassica na- pus to pathogen stress — elicited by the fungal necrotroph Sclerotinia sclerotio- rum — but also how this response manifested in its parental species, Brassica rapa and Brassica oleracea, and a resynthesized allopolyploid B. napus formed directly from these species. This allowed me to identify a distinct bias to towards the B. oleracea-derived genome in both polyploids, which consequentially influenced the defence response of B. napus.

Recommended citation: de Jong et al. 2023 https://onlinelibrary.wiley.com/doi/10.1111/tpj.16127

Decoding Plasticity Regulators and Transition Trajectories in Glioblastoma with Single-cell Multiomics

Published in bioRxiv, in review, 2025

Glioblastoma (GB) is one of the most lethal human cancers, marked by profound intratumoral heterogeneity and near-universal treatment resistance. Cellular plasticity, the capacity of cancer cells to transition between phenotypic states, drives GB progression and resistance. However, the regulatory logic that permits or restricts specific state transitions remains poorly understood. Here, we integrated single-nucleus RNA and chromatin accessibility multi-ome profiles from over one million cells across primary IDH-wildtype GBs and developed scDORI, a scalable deep-learning framework to infer enhancer-driven gene regulatory networks (eGRNs) at single-cell resolution. Our analysis revealed a structured hierarchy of GB cell states governed by distinct regulatory programs, with marked variability in epigenetic plasticity that enables or constrains transitions. Neuronal-like tumor cells emerge as a low plasticity state that deploys active repression, in contrast to more permissive progenitor-like and astrocytic states. We identified the neuronal-like state-specific repressor MYT1L as a key regulator that silences master transcription factors of alternative states. MYT1L gain-of-function in patient-derived GB cells reduced chromatin accessibility, induced neuronal-like identity, and restricted proliferation and invasion in vivo, whereas loss-of-function reactivated plasticity and accelerated malignant features. Our findings delineate the epigenetic architecture and associated transcriptional master regulators that shape GB state trajectories, and establish safeguard repressors such as MYT1L as potential therapeutic targets to constrain malignant plasticity.

Recommended citation: Saraswat et al. 2025 https://www.biorxiv.org/content/10.1101/2025.05.13.653733v1

A spatiotemporal cancer cell trajectory underlies glioblastoma heterogeneity

Published in bioRxiv, in review at Nature, 2025

Cancer cells display highly heterogeneous and plastic states in glioblastoma, an incurable brain tumour. However, how these malignant states arise and whether they follow defined cellular trajectories across tumours is poorly understood. Here, we generated a deep single cell and spatial multi-omic atlas of human glioblastoma that pairs transcriptomic, epigenomic and genomic profiling of 12 tumours across multiple regions. We identify that glioblastoma heterogeneity is driven by spatially-patterned transitions of cancer cells from developmental-like states towards those defined by a glial injury response and hypoxia. This cellular trajectory regionalises tumours into distinct tissue niches and manifests in a molecularly conserved manner across tumours as well as genetically distinct tumour subclones. Moreover, using a new deep learning framework to map cancer cell states jointly with clones in situ, we show that tumour subclones are finely spatially intermixed through glioblastoma tissue niches. Finally, we show that this cancer cell trajectory is intimately linked to myeloid heterogeneity and unfolds across regionalised myeloid signalling environments. Our findings define a stereotyped trajectory of cancer cells in glioblastoma and unify glioblastoma tumour heterogeneity into a tractable cellular and tissue framework.

Recommended citation: de Jong et al. 2025 https://www.biorxiv.org/content/10.1101/2025.05.13.653495v1

talks

Introduction to RNA-Seq informatics

Published:

A multi-session tutorial educating students on the fundamentals of RNA-seq informatics (analytical workflow, pipeline construction, and common tools.

A survey of ancient paralog alternative splicing patterns in Arabidopsis thaliana root cell-types

Published:

Whole-genome duplication events have played an extensive role in the evolution of flowering plants. The sudden doubling of genetic material can expedite large scale changes in gene function and expression patterns. Alternative splicing (AS) offers an avenue with which genes duplicated in polyploidy events (homeologs) may contribute to such functional diversity. AS produces multiple transcript isoforms through the differential removal of introns from the primary mRNA transcript. This process contributes to the function complexity of the cell by expanding both proteomic diversity and mechanisms of post-transcriptional regulation. While there is evidence of considerable divergence in alternative splicing between homeologous genes, the extent to which these differences manifest in different tissue-types is less understood. Using RNA-Seq data I have surveyed the transcriptomes of root tissues in paleopolyploid Arabidopsis thaliana. Assessing the distribution of splicing events between homeolog pairs, I am determining the extent of homeologous AS divergence across multiple zones of root development. Consequently, I have identified a high degree of asymmetry in alternative splicing patterns between several gene pairs. These results will hopefully provide insight into how alternative splicing contributes to tissue-specific variation following gene duplication in plants.

Transcriptomic response of multiple Brassica species to Sclerotinia sclerotiorum infection

Published:

To investigate the interplay between polyploid gene expression and biotic stress response, Brassica napus, Brassica oleracea, Brassica rapa, and a synthetic Brassica napus (formed directly from the aforementioned parental species of B. napus) were subjected to the economically devastating fungus Sclerotinia sclerotiorum. RNA-Seq analysis of these pathosystems revealed wide-spread transcriptomic changes involving both constitutive gene expression and alternative splicing. Cross-species comparisons showed a concerted response between all assayed Brassica species characterized by the up-regulation of jasmonic acid signalling pathways, cell-wall defense genes, chitinases, and pathogen responsive genes. Subgenome comparisons also showed considerable non-parental gene expression patterns in the synthetic Brassica napus, in addition to a C-subgenome expression bias, suggesting transcriptome reprogramming occurs relatively quickly following polyploidization.

A spatiotemporal cancer cell trajectory underlies glioblastoma heterogeneity

Published:

Cancer cells display highly heterogeneous and plastic states in glioblastoma, an incurable brain tumour. However, how these malignant states arise and whether they follow defined cellular trajectories across tumours is poorly understood. Here, we generated a deep single cell and spatial multi-omic atlas of human glioblastoma that pairs transcriptomic, epigenomic and genomic profiling of 12 tumours across multiple regions. We identify that glioblastoma heterogeneity is driven by spatially-patterned transitions of cancer cells from developmental-like states towards those defined by a glial injury response and hypoxia. This cellular trajectory regionalises tumours into distinct tissue niches and manifests in a molecularly conserved manner across tumours as well as genetically distinct tumour subclones. Moreover, using a new deep learning framework to map cancer cell states jointly with clones in situ, we show that tumour subclones are finely spatially intermixed through glioblastoma tissue niches. Finally, we show that this cancer cell trajectory is intimately linked to myeloid heterogeneity and unfolds across regionalised myeloid signalling environments. Our findings define a stereotyped trajectory of cancer cells in glioblastoma and unify glioblastoma tumour heterogeneity into a tractable cellular and tissue framework.

A multi-modal spatiotemporal map of glioblastoma heterogeneity

Published:

Cancer cells display highly heterogeneous and plastic states in glioblastoma, an incurable brain tumour. However, how these malignant states arise and whether they follow defined cellular trajectories across tumours is poorly understood. Here, we generated a deep single cell and spatial multi-omic atlas of human glioblastoma that pairs transcriptomic, epigenomic and genomic profiling of 12 tumours across multiple regions. We identify that glioblastoma heterogeneity is driven by spatially-patterned transitions of cancer cells from developmental-like states towards those defined by a glial injury response and hypoxia. This cellular trajectory regionalises tumours into distinct tissue niches and manifests in a molecularly conserved manner across tumours as well as genetically distinct tumour subclones. Moreover, using a new deep learning framework to map cancer cell states jointly with clones in situ, we show that tumour subclones are finely spatially intermixed through glioblastoma tissue niches. Finally, we show that this cancer cell trajectory is intimately linked to myeloid heterogeneity and unfolds across regionalised myeloid signalling environments. Our findings define a stereotyped trajectory of cancer cells in glioblastoma and unify glioblastoma tumour heterogeneity into a tractable cellular and tissue framework.

teaching

BIOL430: Molecular Evolution

Undergraduate course, University of British Columbia, 2017

Co-ordinated lecture and paper discussions, taught computer tutorials, marked assignments and exams.

BIOL430: Molecular Evolution

Undergraduate course, University of British Columbia, 2018

Co-ordinated group discussion, created assignments and computer lab exercises, taught tutorials, exam invigilation, exam and assignment marking.

BIOL230: Introduction to Ecology

Undergraduate course, University of British Columbia, 2019

Taught student labs, assisted with student report writing, marked assignments and exams.

BIOL306: Advanced Ecology

Undergraduate course, University of British Columbia, 2019

Class title: Introduction to Advanced Ecology.