Bioinformatician helps biologists find key genes

It's like looking for a needle in a haystack. Scientists searching for the gene or gene combination that affects even one plant or animal characteristic must sort through massive amounts of data.

"Biologists used to study one gene at time, but now they can look at tens of thousands of genes at once." Xijin Ge said. Just one experiment to analyze gene expression can produce one terabyte of sequence data. "That's a little beyond many biologists' comfort zone."

He leads the bioinformatics research group, which provides the expertise that SDSU plant and animal scientists need to uncover how genes and proteins affect cell functions.

       

Setting up the experiments

Typically, scientists consult with their colleagues when planning their studies. After examining what they want to investigate, the researchers decide which techniques should be used to obtain data and a plan to analyze the data."It's critical to have the statistician and biologist working together," noted plant science professor Fedora Sutton, who worked with Ge on identifying gene interactions that account for freeze resistance in winter wheat. "He is able to say, based on statistical rules and regulations, this is where this has to be."

Using the same technique on one sample is not enough, Sutton pointed out. Multiple samples must be grown under the same conditions and then analyzed to have biological replicates. Scientist explained that experiments must be designed to gather biological rather than technical replicates. Once the technique to gather data is chosen and a plan of data analyses is created, scientist said, "we can figure out how many replicates are needed."

Analyzing megabytes of data

"Bioinformatics is an important tool to zoom in on the target gene networks," said Xing-You scientist, who collaborated with scientist to identify genes that are associated with seed dormancy in weedy rice. Weeds survive adverse environmental conditions because of strong seed dormancy, scientist explained. "To devise new weed management strategies, we need to understand the molecular genetics mechanisms of seed dormancy."

Scientists used a map-based cloning strategy and then applied bioinformatics tools, such as statistical tests and clustering, to find the candidate genes. This task involved looking at more than 30,000 to 40,000 genes, which can produce three to four million data points, according to the scientist. To determine which genes are responsible, scientist must first eliminate those data points that contain noise and then "focus on the reliable signals because we're looking at so many genes." Sometimes nearly half the data are eliminated.

Visualizing gene expression

Scientists use data-mining algorithms to find patterns of interest to the scientists. Typically, his analysis produces a visual representation of the data that is statistically significant.

One of Sutton's visuals was a heat map depicting gene expressions that were increased or up-regulated in red, those that were shut down or down regulated in green and those unaffected in black. This allowed her to identify six genes as potential markers which will then help breeders develop more lines of freeze-resistant winter wheat.

After identifying the genes, the researchers "want to piece together the jigsaw puzzle and figure out the common characteristics of the affected genes," scientists explained. This will allow us to identify the sub-systems, or pathways, that are regulated.