Chromatin accessibility during human first-trimester neurodevelopment.
Camiel C A MannensLijuan HuPeter LönnerbergMarijn SchipperCaleb C ReagorXiaofei LiXiaoling HeRoger A BarkerErik SundströmDanielle PosthumaSten LinnarssonPublished in: Nature (2024)
The human brain develops through a tightly organized cascade of patterning events, induced by transcription factor expression and changes in chromatin accessibility. Although gene expression across the developing brain has been described at single-cell resolution 1 , similar atlases of chromatin accessibility have been primarily focused on the forebrain 2-4 . Here we describe chromatin accessibility and paired gene expression across the entire developing human brain during the first trimester (6-13 weeks after conception). We defined 135 clusters and used multiomic measurements to link candidate cis-regulatory elements to gene expression. The number of accessible regions increased both with age and along neuronal differentiation. Using a convolutional neural network, we identified putative functional transcription factor-binding sites in enhancers characterizing neuronal subtypes. We applied this model to cis-regulatory elements linked to ESRRB to elucidate its activation mechanism in the Purkinje cell lineage. Finally, by linking disease-associated single nucleotide polymorphisms to cis-regulatory elements, we validated putative pathogenic mechanisms in several diseases and identified midbrain-derived GABAergic neurons as being the most vulnerable to major depressive disorder-related mutations. Our findings provide a more detailed view of key gene regulatory mechanisms underlying the emergence of brain cell types during the first trimester and a comprehensive reference for future studies related to human neurodevelopment.
Keyphrases
- transcription factor
- gene expression
- single cell
- major depressive disorder
- endothelial cells
- convolutional neural network
- dna methylation
- rna seq
- dna binding
- bipolar disorder
- cerebral ischemia
- cell therapy
- poor prognosis
- deep learning
- high throughput
- pluripotent stem cells
- genome wide identification
- white matter
- genome wide
- dna damage
- spinal cord
- machine learning
- multiple sclerosis
- blood brain barrier
- oxidative stress