Golkaram and colleagues set out to identify the patterns and interactions between mRNA and miRNAs, which control and regulate cell development through expressing specific genes. This may give further insight into neurodevelopmental diseases and gene expression patterns. / Courtesy of Pixabay

Every cell in our bodies comes from the same source — namely, germ cells. So how do these cells develop to serve so many different functions in our body? From neural cells with axons over two feet long to skin cells with touch-sensitive hair follicles, the functions vary vastly due to different gene expression. All these cells have the same DNA we were born with, but messenger RNA (mRNA) transcribes the genes while microRNA (miRNA) regulates this process, resulting in many different, highly specific cell types.

Several different departments at UCSB, UCSF and the Indian Institute of Technology recently worked together on an article titled “Regulation of cell-type-specific transcriptomes by microRNA networks during human brain development,” published by Nature Neuroscience in 2018.

The researchers essentially created a library of all mRNAs and miRNAs to identify the differentiation of cell types in the developing brain. These RNA fragments are expressed differently in every cell and are directly associated with the function of a cell. The single stranded mRNA works to transcribe genes into proteins for use in the cell. This gene transcription is regulated by non-coding miRNA which can alter genes after transcription, suppress unnecessary genes and serve as a marker for cell malfunction.

Mahdi Golkaram, the first co-author of this paper explains, “The core hypothesis was that the pattern in this network of microRNAs and mRNAs is related to cell-type specificity.” Golkaram received his PhD in Mechanical Engineering at UCSB in September 2018. He worked in Linda Petzold’s lab to contribute a bioinformatics approach to this paper.

Bioinformatics, the use of computer programming to organize and interpret biological information, can aid in understanding genomics. This analysis enabled researchers to condense and comprehend a large number of mRNAs, miRNAs and all of the patterns between them. These expression patterns can be useful tools in identifying how our cells operate, and in this case, how they develop.

“During development we have only two cells: an egg and a sperm and then they divide. But how do we get to a complex set of cells like the adult brain beginning from only two cells? The distribution of cell types differs significantly, and the ratio of different cell types is very important. The imbalance of this ratio can be pathogenic,” Golkaram said.

In the most basic sense, there are neurons that communicate information with electrical signals and glial cells that assist the neurons by maintaining a precise environment in the brain. An alteration in this ratio can cause disruption in brain function and identifying the RNA expression patterns may help us identify this early in development.

“We can look at disease — for example, autism was one — but there are several different prenatal diseases we can potentially understand by looking at microRNAs. Introducing a mechanistic model that tells you this gene is causing this disorder is the first step to finding a cure,” Golkaram said.

In order to organize such a complex system, Golkaram created a computer-learning program that would recognize patterns in the miRNA and mRNA. These patterns can be used to understand how the cell is differentiating and how it will function in a fully formed adult brain.

In an attempt to simplify the concept, Golkaram explains, “Certain mRNAs and microRNAs tend to have something in common and we found that what they have in common is actually cell types. We showed how they interact to control and regulate cell-type specificity at different locations or different stages of development.”

The lab determined these RNA sequences using qPCR quantitative polymerase chain reaction. Instead of proliferating the genomes of a population of cells, they profiled single cells to find the specific mRNA and miRNA interactions. This single-cell sequencing can further define the differences between individual brain cell types.

Golkaram gives an analogy. “If you want to find an address and we have street addresses, zip codes, apartment numbers, it’s essentially the same thing. We have mRNA expression and now we have miRNA expression. Each of these can be used as important information to determine cell types.”

Cell-type-specific transcripts were presented as a bipartite network, meaning that a single miRNA has access to regulation of many mRNAs, but a single mRNA only has a few miRNAs that operate on it. This was then analyzed by a “bipartite community detection algorithm,” as stated in the paper. The algorithm developed by Golkaram can detect patterns of the interactions between mRNA and miRNA and lead to insight regarding neurodevelopmental disorders.

This emerging “transcriptome” research can reveal a lot about how species differ so greatly when much of our genomes contain the same genetic material.

Golkaram suggests that this research could take an evolutionary turn. “A comparison of a human brain to an ape’s or a monkey’s brain would be a very interesting evolutionary biology question … That could be answered by looking at microRNAs and why certain genes are only expressed in humans but not in apes.”

Each cell in our body contains the same DNA — our genomic blueprint — so this gene expression is crucial to understanding cell function. This experiment has provided strong insight into the patterns of expression in brain cells and could lead to a better understanding of diseases in early brain development.