NIEHS scientists developed an application that enables users to quickly assess gene interactions without having a background in computer programming or statistical modeling. Structural Equation Modeling of In silico Perturbations (SEMIPs), which was created using the open-source R Shiny platform, will help researchers form hypotheses and features a testing procedure to assess statistical significance.

Wu’s group, which is led by Francesco DeMayo, Ph.D., aims to understand how the environment can affect the reproductive tract and pulmonary function. (Photo courtesy of Steve McCaw / NIEHS)

SEMIPs uses what are known as reporter genes to indicate the cause of a given change in gene expression or activity. The process is comparable to assessing liver or kidney function from a routine blood draw, which can reveal organs’ condition without requiring invasive surgery. The application will save time and resources while maintaining scientific rigor.

The tool shines in its ability to help researchers compare gene expression changes in model organisms with those in humans, according to Steve Wu, Ph.D., a staff scientist in the institute’s Pregnancy and Female Reproduction Group.

“We try to estimate the activity of genes of interest, and then we look at the interaction between those genes,” he said. “We ask, ‘Would these interactions in the model organism be present in a human?’ The application enables you to mathematically estimate whether it is possible that a specific interaction is occurring in both the human and the experimental model.”

Saving time, lowering costs

SEMIPs holds great promise in numerous research and clinical scenarios, including in vitro fertilization (IVF), noted Wu. He gave the example of a group of researchers in Spain who completed an exhaustive clinical sampling process to narrow down a panel of 238 genes and test whether a patient would have success with IVF. SEMIPs will help scientists better determine which genes to test, significantly reducing time and cost.

“This mathematical approach is the first step to narrow down the genes we look at and make a more affordable system to look at the information,” Wu said. “If you have a way to tell patients what their odds are of being able to get pregnant and whether the time is right physiologically, you greatly reduce patient suffering and increase the chances of getting where they want to go.”

He added that in the future, SEMIPs could be used to formulate hypotheses that lead to the development of new contraceptives.

Mining data, gaining new insights

Li manages the Integrative Bioinformatics Support Group to provide computational and analytical assistance to the NIEHS research community. (Photo courtesy of Steve McCaw / NIEHS)

One of Wu’s collaborators, Jian-Liang Li, Ph.D., director of the NIEHS Integrative Bioinformatics Support Group, said that in addition to its scientific impact, the new application is notable because it was developed in an interdisciplinary environment. Bench scientists, statisticians, and bioinformatics researchers all collaborated on the project.

“Our new application shows that team-based research is a group effort that requires skills and knowledge from many different backgrounds,” Li said.

He added that approaching scientific research from multiple angles can generate new insights from publicly available data. The application itself also makes research easier for scientists without backgrounds in structural equation modeling.

“This user-friendly model is a tool that can help researchers generate a hypothesis to guide a lab experiment using existing data,” Li said.

Citation: Li J, Bushel PR, Lin L, Day K, Wang T, DeMayo FJ, Wu SP, Li JL. 2021. Structural equation modeling of in silico perturbations. Front Genet. 12:727532.

(Kelley Christensen is a contract writer and editor for the NIEHS Office of Communications and Public Liaison.)