Skip to main content
Premium Trial:

Request an Annual Quote

Penn State Researchers Seek to License Model to Predict Crossovers in DNA Shuffling


Costas Maranas and his colleagues at Pennsylvania State University are developing a computational method for predicting the number and locations of crossovers that occur in DNA shuffling, a process that mixes genetic material from different parent sequences in order to identify which genes produce desirable products.

While DNA shuffling is commonly used to generate combinatorial libraries for novel protein design, currently available experimental techniques are labor-intensive and costly. Maranas said that the predictive models he has created to quantify the outcome of these experiments would help researchers identify the best experimental route.

“We used thermodynamics and reaction engineering to evaluate and model this complex reaction network so we can now predict where the DNA from different parent genes will combine,” said Maranas.

The model studied how fragment length, annealing temperature, sequence identity, and the number of shuffled parent sequences affect the number, type, and distribution of crossovers along the length of reassembled sequences. The more similar genes are, the more potential for crossover exists.

“If the sequences are very different and the experiment is done at high temperature, there will be no crossovers at all,” said Maranas. Fragment size also can affect the number of crossovers.

Comparisons with experimental data have shown a high level of agreement. “At minimum, we can predict whether no crossovers, a few crossovers or many crossovers will be generated,” said Maranas.

Maranas said that the University is negotiating licensing agreements with several directed evolution companies interested in using the model as a predictive tool to optimize their protocols.

The researchers are currently studying crossover prediction in other protocols, which unlike DNA shuffling, can be used to recombine sequences with very low sequence identy. Maranas also said the new technique would work in cases where bits and pieces of parent sequences are shuffled rather than the entire length.

— BT

Filed under

The Scan

Test of the China Initiative

According to Science, the upcoming trial of Harvard University chemist Charles Lieber will test the US China Initiative.

Collaborative Approach

A virologist who spotted the Omicron variant of SARS-CoV-2 tells the Associated Press that its detection was aided by scientific sharing.

Genes of a Guide Dog

Wired reports on a study aimed at uncovering genes involved in being a successful guide dog.

PLOS Papers on RNAs in Metastatic Prostate Cancer, Ebola Field Lab, Embryonic RNA Editing

In PLOS this week: circRNA-mediated ceRNA network points to prostate cancer biomarkers, Ebola testing at frontline field laboratory, and more.