In a world-first, Western Australian scientists have successfully mapped the development of a ‘normal’ human brain cell.
The map shows gene activity changes in diverse human brain cell types from pre-birth to adulthood, enabling researchers to identify altered states more accurately in neurological and psychiatric disorders such as schizophrenia, or aberrant cell states in diseases such as brain cancer.
The research, published 1 November 2022 in the journal Cell, addresses a major gap in the scientific knowledge of gene activity (and the factors controlling it) that occurs in the brain as an individual grows and develops, and was spearheaded by a team of Perth researchers from UWA and the Harry Perkins Institute of Medical Research.
Lead author, Professor Ryan Lister, who developed the first comprehensive maps of the human epigenome, explained that the human brain contains billions of cells, encompassing a huge diversity of different cell types – each with their own specialised functions – which takes almost three decades to mature.
“Through this lengthy process our cognitive abilities emerge, grow, change, and advance. Think of the enormous differences in what an adult can do, compared to a child, toddler, or newborn,” Professor Lister said.
“Underpinning these advances are complex changes in the cells of our brain, as they migrate, grow, form, and refine connections, and communicate; and importantly, these changes require the correct control and timing of gene activity, and our new work provides the first reference map of this.
“This high-resolution map shows how the gene activity of each different type of brain cell in the prefrontal cortex changes as we mature, from mid-gestation through to adulthood in normal individuals, and predicts the cellular factors that control these changes.”
“Without a map of normal development, we don’t have a reference to identify what is abnormal, and how it might contribute to brain disorders.”
The team (including Dr Chuck Herring, Dr Rebecca Simmons, Dr Saskia Freytag and Dr Daniel Poppe) performed single-nucleus RNA-seq (snRNA-seq) profiling of 26 post-mortem PFC samples from individuals spanning foetal, neonatal, infancy, childhood, adolescence, and adult stages of development, providing extensive sampling of stages that had been poorly represented in previous single-cell studies.
From this, 154,748 single nuclei transcriptome profiles were generated and used to assemble an integrated developmental reference with distinct chronological ordering of all major neural lineages.
The team identified 86 distinct clusters across all the developmental stages, which were annotated by separating nuclei into either excitatory principal neurons or inhibitory interneurons; medial ganglionic eminence, caudal ganglionic eminence, or glia; followed by further separation of the major clusters using layer and subtype-specific marker genes.
“This developmental map revealed systematic expression changes through postnatal development and temporal changes in cell-type abundance, such as expansion of oligodendrocytes from ODC precursor cells beginning in infancy and progressing to adulthood,” the authors explained.
“We further identified modules representing the organized co-expression of multiple genes in various subsets of nuclei, [and] each module reflects cell-type-specific transcriptional changes aligning with known cell functions and processes that occur during brain development.”
These co-expression modules represent the broad cell states and dynamics of the PFC, capturing major cell types and their functions, developmental processes, and cell-type-specific expression changes throughout brain development.
“These maps are helping us to better understand brain disorders, and to develop improved models of brain cells for modelling diseases and new drug discovery.” Professor Lister said.
“It will be a great resource for neurologists, neuroscientists, and those working in developmental biology,” Dr Poppe added.
“Most disorders affecting the brain progress over time, so these findings could allow researchers to identify initial events before these diseases manifest and would enable earlier intervention in the future.”