Biology subjects

Jourdon, A.

Publications and source records attributed to Jourdon, A..

3 recordsLinked to original sources

bioRxiv2023

Enhancer-driven regulatory network of forebrain human development provides insights into autism

Cell differentiation is orchestrated by transcription factors (TFs) binding to enhancers, shaping gene regulatory networks that drive neuronal lineage specification. Deciphering these enhancer-driven networks in human forebrain development is essential for understanding the genetic basis of neurodevelopmental disorders. Through integrative epigenomic and transcriptomic analyses of human forebrain organoids derived from 10 individuals with autism spectrum disorder (ASD) and their neurotypical fathers, we constructed a comprehensive enhancer-driven gene regulatory network (GRN) of early neurodevelopment. This GRN revealed hierarchical regulatory transitions guiding neuronal differentiation and was experimentally validated via CRISPR interference (CRISPRi) and loss-of-function analyses. A subnetwork linked ASD-associated transcriptomic alterations to dysregulated TF activity, implicating FOXG1, BHLHE22, EOMES, and NEUROD2 as key regulators of excitatory neuron specification in macrocephalic ASD. These findings suggest that ASD disrupts enhancer-driven regulatory frameworks, altering neuronal cell fate decisions in the developing fetal brain.

genomics↗

bioRxiv2023

Evaluating performance and applications of sample-wise cell deconvolution methods on human brain transcriptomic data

Sample-wise deconvolution methods have been developed to estimate cell-type proportions and gene expressions in bulk-tissue samples. However, the performance of these methods and their biological applications has not been evaluated, particularly on human brain transcriptomic data. Here, nine deconvolution methods were evaluated with sample-matched data from bulk-tissue RNAseq, single-cell/nuclei (sc/sn) RNAseq, and immunohistochemistry. A total of 1,130,767 nuclei/cells from 149 adult postmortem brains and 72 organoid samples were used. The results showed the best performance of dtangle for estimating cell proportions and bMIND for estimating sample-wise cell-type gene expression. For eight brain cell types, 25,273 cell-type eQTLs were identified with deconvoluted expressions (decon-eQTLs). The results showed that decon-eQTLs explained more schizophrenia GWAS heritability than bulk-tissue or single-cell eQTLs alone. Differential gene expression associated with multiple phenotypes were also examined using the deconvoluted data. Our findings, which were replicated in bulk-tissue RNAseq and sc/snRNAseq data, provided new insights into the biological applications of deconvoluted data.

genomics↗

bioRxiv2022

ASD modelling in organoids reveals imbalance of excitatory cortical neuron subtypes during early neurogenesis

There is no clear genetic etiology or convergent pathophysiology for autism spectrum disorders (ASD). Using cortical organoids and single-cell transcriptomics, we modeled alterations in the formation of the forebrain between sons with idiopathic ASD and their unaffected fathers in thirteen families. Alterations in the transcriptome suggest that ASD pathogenesis in macrocephalic and normocephalic probands involves an opposite disruption of the balance between the excitatory neurons of the dorsal cortical plate and other lineages such as the early-generated neurons from the putative preplate. The imbalance stemmed from a divergent expression of transcription factors driving cell fate during early cortical development. While we did not find probands genomic variants explaining the observed transcriptomic alterations, a significant overlap between altered transcripts and reported ASD risk genes affected by rare variants suggests a degree of gene convergence between rare forms of ASD and developmental transcriptome in idiopathic ASD.

neuroscience↗