Simple trick can improve accuracy of plant genetics research

Researchers have published a simple trick that improves the accuracy of techniques that help us understand how external variables – such as temperature – affect gene activity in plants.

“There are really two contributions here,” says Colleen Doherty, corresponding author of a paper on the work and an associate professor of molecular and structural biochemistry at North Carolina State University. “First, we are raising the visibility of a problem that many of us in the plant research community were unaware of, as well as highlighting the solution. Second, we have demonstrated that addressing this problem can make a significant difference to our understanding of gene activity in plants.”

At issue is a technique called RNA-seq analysis, which is used to measure changes in gene activity—eg, when genes are actively transcribed to make proteins.

“We use RNA-seq analysis to assess how plants respond to different stimuli or changes in their environment,” says Doherty. “It’s widely used because it’s a relatively easy and inexpensive way to monitor plant responses.”

For example, researchers can use RNA-seq analysis to see which genes are activated when a plant is experiencing drought conditions, which then informs the development of new plant varieties that are drought-resistant.

But there is a specific challenge associated with RNA-seq analysis that Doherty and her collaborators ran into by chance.

“We were monitoring how plants respond to different temperatures at different times of the day, and the results we got were wildly different,” says Doherty. “At first we thought we might be doing something wrong. But when we started looking into it, we learned that animals and yeast are known to have global changes in transcription based on variables such as time of day or nitrogen deprivation.

In other words, researchers want to see how specific variables – such as increased temperature – affect transcription in specific genes. But there are some variables – like the time of day – that can increase or decrease transcription everything genes. This can impair researchers’ ability to draw conclusions about the specific variables they want to study.

“Fortunately, we found that this problem is sufficiently established among researchers working in non-plant species that they have developed a method to account for it, called ‘artificial spike-in,'” says Doherty. “These and similar techniques have been used in plant science in other contexts and when using older techniques and technologies. But for whatever reason, our field did not include artificial endpoints in our methodology when we adopted RNA-seq analysis.

Artificial spikes use pieces of foreign RNA that don’t resemble anything in the plant’s genome, meaning that the foreign RNA won’t be confused with anything the plant itself produces. The researchers introduce the foreign RNA into the analysis process at the beginning of the experiment. Because global changes in transcription will not affect the foreign RNA, it can be used as a fixed reference point that allows researchers to determine the degree to which there is an overall increase or decrease in the RNA that itself the plant is producing.

“When we used artificial spikes to calculate global changes in transcription, we found that the changes in plants exposed to temperature changes at different times of the day were actually even greater than we expected,” says Doherty.

“Artificial understanding gave us more precise information and greater insight into how plants behave at night – as we found that global transcription was higher at night. Before we adopted the use of artificial spike-ins, we missed a lot of what was going on at night.

“Artificial intelligence is an elegant solution to a challenge that many of us in the plant research community didn’t even know was there,” says Doherty. “We are optimistic that this technique will improve the accuracy of transcriptional analysis across a wide variety of conditions that can affect global transcription in plant species. And this, in turn, can help our research community gather new knowledge about the species we study.

“We didn’t develop this solution – the artificial spike – but we really hope it gains wider use in plant science.”

This article was reprinted from North Carolina State University News. Read the original here.