An algorithm is sped up to predict harmful effects from specific gene mutations

May 6, 2016, Agency for Science, Technology and Research (A*STAR), Singapore

In 2001, researchers developed a formula, or algorithm, that predicts whether a specific change in a gene sequence can result in harmful effects. While useful, the algorithm was slow; the computations underpinning these predictions used multiple central processing units (CPUs) and a significant amount of time. Now A*STAR researchers have adapted the algorithm to work on a graphical processing unit, a specialized electronic circuit that can process huge amounts of data in parallel.

The faster computational time has allowed the team to expand their "database of predictions" from just the human genome to include more than 200 additional organisms.

Similarities exist between the same of different organisms. Even so, individual organisms have differences in parts of their genomes when compared to other organisms of the same species. Some of these differences affect how proteins function and may lead to disease. By comparing genetic sequences, researchers are able to pinpoint disease-causing gene mutations. But this requires sifting through huge amounts of data.

The SIFT (Sorting Intolerant From Tolerant) predicts which changes in a gene — known as variants — could affect the function of the protein that gene encodes. Using SIFT, A*STAR researchers computed potential changes that can occur to gene sequences in humans to compile a database of predictions. Researchers provide SIFT with the gene variants they are investigating as a possible source of disease. SIFT then looks up the variants in its database of predictions. Variants that are predicted deleterious by SIFT are highlighted and may be considered worthy of further investigation.

Compiling SIFT's database for the involved performing computations on multiple CPUs, which took about four minutes to analyse a single gene sequence.

"I had wanted to make SIFT databases for a lot more organisms, but making the human database took significant time," says systems biologist Pauline Ng from the Genome Institute of Singapore.

SIFT was adapted for use with a to make faster predictions. This allowed the team to expand the scope of the algorithm's predictions to cover more than 200 other organisms. SIFT 4G, the updated algorithm, takes only 2.6 seconds to analyse a compared to SIFT's four minutes.

The updated and algorithm will not only facilitate the identification of disease-causing gene mutations but will help researchers understand the genetic variations that make some animal breeds or plants strains more robust or prone to disease.

Explore further: Yeast against the machine: Bakers' yeast could improve diagnosis

More information: Robert Vaser et al. SIFT missense predictions for genomes, Nature Protocols (2015). DOI: 10.1038/nprot.2015.123

Related Stories

Yeast against the machine: Bakers' yeast could improve diagnosis

April 6, 2016
It's easier than ever to sequence our DNA, but doctors still can't exactly tell from our genomes which diseases might befall us. Professor Fritz Roth is setting out to change this by going to basics—to our billion-year-old ...

Genetic risk factors of disparate diseases share similar biological underpinnings

April 28, 2016
The discovery of shared biological properties among independent variants of DNA sequences offers the opportunity to broaden understanding of the biological basis of disease and identify new therapeutic targets, according ...

Recommended for you

Study of smoking and genetics illuminates complexities of blood pressure

February 15, 2018
Analyzing the genetics and smoking habits of more than half a million people has shed new light on the complexities of controlling blood pressure, according to a study led by researchers at Washington University School of ...

New mutation linked to ovarian cancer can be passed down through dad

February 15, 2018
A newly identified mutation, passed down through the X-chromosome, is linked to earlier onset of ovarian cancer in women and prostate cancer in father and sons. Kunle Odunsi, Kevin H. Eng and colleagues at Roswell Park Comprehensive ...

A gene that increases the risk of pancreatic cancer controls inflammation in normal tissue

February 14, 2018
Inflammation is a defensive response of the body to pathogens, but when it persists, it can be harmful, even leading to cancer. Hence, it is crucial to understand the relationship between inflammation and cancer. A group ...

Scientists develop low-cost way to build gene sequences

February 13, 2018
A new technique pioneered by UCLA researchers could enable scientists in any typical biochemistry laboratory to make their own gene sequences for only about $2 per gene. Researchers now generally buy gene sequences from commercial ...

New insights into gene underlying circadian rhythms

February 13, 2018
A genetic modification in a "clock gene" that influences circadian rhythm produced significant changes in the length and magnitude of cycles, providing insight into the complex system and giving scientists a new tool to further ...

Clues to aging found in stem cells' genomes

February 13, 2018
Little hints of immortality are lurking in fruit flies' stem cells.

0 comments

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.