This web page was produced as an assignment for an undergraduate course at Davidson College.
The regions associated with brain disorders vary therefore it can be hypothesized that the turning off and on genes (gene expression) in different parts of the brain is crucial to how brain diseases affect specific regions of the brain. Evidence was found to support the hypothesis that genes with variations in different regions of the brain play a distinct role in brain development and function, and DNA methylation might influence the variation in genes across the brain.
Genetic diversity within the human brain is an example of its complexity. The brain is an important part of the nervous system and understanding the effect of diversity is key to comprehending brain function. Gene isoforms are an element of genetic diversity in the brain, these are variations in the gene sequence that produce different mRNA 1, think of a recipe that has multiple variations, it is the same recipe but each variation creates a slightly different final dish. Different regions of the brain are affected in neurological and neuropsychiatric diseases and differences in gene expression could explain this phenomenon. However, only a few studies have been done to study gene expression in different regions of the human brain. Prior to this study, it was hypothesized that changes in neurotransmitters, protein homeostasis, and energy demand were associated with what brain regions diseases affect, however more study needed to be done on detailed mechanisms such as synaptic connections and gene expression patterns. The researchers wanted to understand how gene expression and gene isoform patterns vary across different regions of the brain. They used long read sequencing of RNA to study three regions of the human brain. Sequencing regions of the brain to study gene expression is important because neurological and neuropsychiatric disorders affect specific regions of the brain, studying gene expression in these regions can help identify molecular changes associated with these disorders.
Brain disorders such as schizophrenia, Alzheimers, bipolar disorder etc all have grave effects on human morbidity and mortality. The researchers used long-read sequencing technology to answer their questions. Long read sequencing reads the start of the RNA molecule (5′) to the end of the molecule (3′), as well as the polyA tail which is like a marker that signals the end of the molecule. 2 The 5′ and 3′ are referred to as Untranslated Regions because they are not translated into a protein during protein synthesis, however they contain important elements that control gene expression. They performed this sequencing on three regions (temporal cortex, hypothalamus, and cerebellum) extracted from the postmortem human brain of 3 males in their 50s and focused on unique patterns of gene expression.
Another factor that influences gene expression is DNA methylation. DNA methylation is a form of chemical modification of DNA, it involves the transfer of a methyl group onto the C5 position of the cytosine to form 5-methylcytosine. DNA methylation regulates gene expression by recruiting proteins involved in gene repression 3. DNA methylation can enhance or suppress gene expression. They performed an analysis of long read RNA sequencing and DNA methylation to examine the effect of DNA methylation on alternative splicing (alternative splicing contributes to the generation of gene isoforms)4.
The cerebellum showed distinct patterns of gene expression, while the hypothalamus and temporal cortex exhibited similar levels of gene expression. The cerebellum had significantly fewer isoforms compared to the hypothalamus and temporal cortex. Interestingly, a significant proportion of these isoforms (42.9%) were not previously registered in reference databases and were found to be expressed in all three brain regions. However, a higher proportion of isoforms (61.2%-82.2%) were expressed in one or two regions, indicating region-specific gene expression patterns. The average number of isoforms per gene was 2.74, isoform lengths peaked at around 3kb, and slightly shorter lengths were observed in the hypothalamus. Transcript per million was used to measure gene expression and 201 genes with TPM greater than 200 were identified. Myelin basic protein was the most highly expressed gene across the brain. Gene expression in each brain region was examined and similar trends were observed, many highly expressed genes in each region were associated with pathways related to brain and nervous system development. Genes that were uniquely expressed in each brain region were identified. 42 genes in the cerebellum, 25 in the hypothalamus, and 44 in the temporal cortex. Pathway analysis detected no significant pathways in the cerebellum and hypothalamus, while synaptic signaling-related pathways were identified in the temporal cortex.
DNA methylation was investigated to determine its role in the usage of different isoforms in various regions of the brain. They found that there were significantly more differentially methylated positions and regions near genes that displayed different isoform usage across different brain regions. These sites were enriched in the upstream regions (5`) of genes. The structural differences of isoforms were examined and it was discovered that DMPs were prolific in the downstream of the transcription start site between isoforms that had different first exons. It was noted that previous studies suggested that DNA methylation is associated with gene expression and alternative splicing, however there was no evidence that supported a direct correlation between methylation and isoform differences.
Although this study gave answers to previous questions, it also created some new questions. How do changes in gene expression contribute to the progression of brain disorders? How do environmental factors interact with genetic factors to influence gene expression? A societal implication of the study is that it can increase stigmatization against individuals with brain disorders. The main weakness of the study is the sample size, it was very small and limited to one gender, because of this there could be gender specific differences that were not discovered because only males were included in the study. The researchers addressed this concern in the paper, agreeing that further research with a larger sample size needs to be done.
References
- Liang, M., Raley, C., Zheng, X. et al. Distinguishing highly similar gene isoforms with a clustering-based bioinformatics analysis of PacBio single-molecule long reads. BioData Mining 9, 13 (2016). https://doi.org/10.1186/s13040-016-0090-8
- Mihoko Shimada et al. Identification of region-specific gene isoforms in the human brain using long-read transcriptome sequencing. Sci. Adv.10,eadj5279(2024).DOI:10.1126/sciadv.adj5279
- Moore LD, Le T, Fan G. DNA methylation and its basic function. Neuropsychopharmacology. 2013 Jan;38(1):23-38. doi:10.1038/npp.2012.112
- Kim, H.K., Pham, M.H.C., Ko, K.S. et al. Alternative splicing isoforms in health and disease. Pflugers Arch – Eur J Physiol 470, 995–1016 (2018). https://doi.org/10.1007/s00424-018-2136-x
© Copyright 2022
Department of Biology, Davidson College, Davidson, NC 28036
Shalom Olugbodi
sholugbodi@davidson.edu
This is super interesting! It makes a lot of sense that different regions of the brain that have different functions would also have different expressions. The brain is such a fascinating and complex organ, and it is so cool how such seemingly minuscule changes in expression can lead to such dramatic effects, as seen in neurodegenerative disorders. I am curious about how these scientists chose certain aspects of their experimental design. For one, why did they conduct bulk tissue sampling instead of isolating specific cells from the specific regions of the brain? Bulk sampling seems messy for determining such specific differences, and I think seeing single-cell data and comparisons from these regions could be really interesting. Similarly, I am curious about how much of the RNA degrades post mortem and if obtaining “more fresh” samples could lead to more accurate data (although there may be some ethical issues there admittedly).
Great read, I like the way this post was structured and the way the recipe metaphor was used to explain isoforms and genetic modifications. I like the way they went about their experimental question, in which they wanted to scan different regions of the brain for unique gene expressions. I too hope this would set the basis for a much larger study including diverse samples across men and women at different ages. I also agree that the study suffers discrepancy from mortem samples, but the effort to gain insights into the molecular mechanisms of brain function is still a fascinating feat. I like your inclusions of future directions as this is what I find the most interesting in studies such as these.
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