Computational tool can help study APA mechanism that regulates gene expression

Scientists keen on solving the regulation of genes implicated in human health and disease are widening their horizons by closely analyzing alternative polyadenylation (APA)—an understudied mechanism that controls the expression of genes.

APA is about modifying one of the ends, called the 3-prime end (3′end), of RNA strands that are transcribed from DNA. The modification consists of changing the length of a tail of adenosines, one of the RNA building blocks, at the 3′end before RNA is translated into proteins. This adenosine chain helps to determine how long the messenger RNA lasts in the cell, influencing how much protein is produced from it.”

Dr Hari Krishna Yalamanchili, Study First Author, Baylor College of Medicine

Dr Yalamanchili is also a postdoctoral associate in the laboratory of Dr Zhandong Liu at Baylor College of Medicine.

The researchers’ interest in APA has led to the development of many 3′ sequencing (3′Seq) methods that enable accurate detection of APA locations on RNA strands. However, the scientists overlooked a strong computational tool that is particularly developed to investigate the wealth of the generated 3′Seq data.

Meet PolyA-miner

Until now, researchers have been using traditional RNA sequencing computational tools to analyze the 3′Seq datasets. Although this approach produces results, it does not maximize the potential amount of information that can be extracted from that data. Here we developed a computational tool that precisely analyzes 3′Seq data. We call it PolyA-miner.”

Dr Hari Krishna Yalamanchili, Study First Author, Baylor College of Medicine

Using the new computational tool, Yalamanchili and his collaborators investigated the existing 3′Seq datasets and found that PolyA-miner not only recreated the analyses realized with standard computational tools but also detected novel APA locations that were not identified with other analytical methods.

“We were surprised when the PolyA-miner analysis of a glioblastoma cell line dataset identified more than twice the number of genes with APA changes than were initially reported,” Dr Yalamanchili added.

I think that the most exciting part of this new tool is that it enables us to precisely reflect gene-level 3′ changes and to identify many more APA events than before. With other analytical approaches, we underestimate the effect and number of poly-adenylation events.”

Dr Zhandong Liu, Associate Professor, Department of Pediatrics and Neurology, Baylor College of Medicine

Dr Liu also works at the Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital.

Immediate applications

This advancement holds enormous implications for fundamental research and for possibly translating scientific results into clinical settings. APA is regarded as a significant mechanism for the regulation of RNAs that have strong relevance in cancer as well as neurological disorders.

PolyA-miner can help researchers looking to detect the genetic causes of these disorders by establishing whether there are variations in APA between normal and diseased cells.

Armed with this latest analysis, researchers can take a new look at the prevailing genomic datasets that may offer a solution to the cause of human diseases and also help study the recently developed datasets.

“Previously, people knew about APA changes, but did not consider them to be major contributors to gene regulation mainly because we lacked the computational tools to determine APA’s overall influence on gene expression. PolyA-miner has shown that APA seems to play a larger role in gene regulation than we had previously thought,” Dr Yalamanchili concluded.