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're raising the visibility of a problem that many of us in the plant research community were unfamiliar with, as well as highlighting the solution.
For example, researchers can use RNA-seq analysis to see which genes are turned on when a plant is experiencing drought conditions, which then informs the development of new plant varieties that are drought resistant. 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 time of day -- that can increase or decrease transcription inthe genes. This can throw off researchers' ability to draw conclusions about the specific variables they want to study.
"When we used artificial spike-ins to account for global changes in transcription, we found that the differences in plants exposed to temperature changes at different times of day were actually even greater than we anticipated," Doherty says. "We didn't develop this solution -- artificial spike-ins -- but we really hope it garners more widespread use in plant science."
A normalization method that controls for total RNA abundance affects the identification of differentially expressed genes, revealing bias toward morning‐expressed responsesControlling gene activity is important for engineering plants for improved bioenergy crops and other applications. This research developed synthetic genes that use Boolean logic gates to achieve ...
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