Twenty-first century neuroscience is an enticing field of research that offers the potential to deliver novel insights into the cognition of the human brain and the molecular mechanisms behind brain diseases. However, it needs a little help.
The brain is immensely complex, comprised of functionally diverse anatomical regions which contain a multitude of different cell types. We know that, in order for these varying cell types to serve their function, an array of genes must be differentially expressed throughout the brain; specific genes are switched off in certain areas and certain genes are turned on in others.
We need to be able to look at the brain through a genomic lens to assess how genes are regulated – or dysregulated in the case of some pathologies – to gain a holistic view of its function.
The marriage of neuroscience and genomics has birthed a growing research area known as neurogenomics, which aims to understand how the genome contributes to the evolution, structure, development and function of the nervous system through the analysis of regulatory and transcriptional processes.
The advent of single cell RNA sequencing (scRNA-seq) has made this feat possible. This technique, which continues to be optimized, provides RNA expression profiles of individual cells. Conventionally, bulk RNA sequencing was the "gold standard" technology for the job; however, in mixed cell populations the measurements obtained from bulk RNA sequencing can miss significant differences between individual cells.
More recently, developments in single nuclei RNA sequencing (sNuc-Seq) have propelled the field of neurogenomics even further. Now, researchers can isolate nuclei from particular cells to profile gene expression within that cell – an elegant alternative to scRNA-seq for cells that are difficult to isolate.
A team of scientists led by Philip Khaitovich, a professor at the Skoltech Center for Life Sciences, has conducted a large-scale analysis of gene expression in 33 different regions of human, chimpanzee, macaque and bonobo brains, adopting a mixture of bulk RNA seq and sNuc-Seq. From the data, they have created transcriptome maps of these brain regions, which they hope will be useful in human evolution research. The study is published in the journal Genome Research.
“We are not the first to look into gene expression in the brain. This is an important area of research that someday will shed more light on how human consciousness appeared. However, the tricky point here is that there can be two possible reasons for evolutionary changes in expression: a change in the cellular structure in some area of the brain or a change in the expression of genes in the cells. Previously, scientists could not draw the line between these two possibilities, and now, with the advanced single-cell-resolution method, we finally did it! Our new findings will help better understand the ins and outs of the evolution of gene expression on a more subtle level that was unavailable till now.” - Ekaterina Khrameeva, the first author of the paper and an assistant professor at the Skoltech Center for Life Sciences.
The study results demonstrate that the distribution of human-specific expression differences that separate us humans from non-human primates in the study are not uniform across the 33 brain regions that were analyzed. Rather, the data suggests a complex pattern of expression in the human brain, involving regions such as the cerebral cortex, hypothalamus, and cerebellar gray and white matter. The fact that these differences are most distinctive in humans implies they undergo faster evolution.
When looking at the cellular level, the scientists detected multiple expression differences between species with each of the cell types. This extended to non-neuronal cell types, where there was a substantially greater excess of human-specific expression differences in examined brain regions when compared to neurons, including astrocytes and oligodendrocyte progenitors.
The researchers were also able to decipher information on the sensitivity of the techniques adopted in the study.
Whilst multiple expression differences were detected between species within each cell type, approximately one third of these differences could be detected using bulk RNA-seq method; the remaining differences were only detectable using sNuc-Seq.
Whilst the cell-type-specific evolution differences observed in the study are indeed novel, the authors note that their findings do concur with the literature. They also identify an important component that they brand as "missing" from their study, which is an analysis of temporal patterns of expression evolution in the developing brain. They suggest this to be the appropriate next step in this research space.
Khrameeva et al. (2020). Single-cell-resolution transcriptome map of human, chimpanzee, bonobo, and 3 macaque brains. Genomics Research. Doi: 10.1101/gr.256958.119