Featured Research

from universities, journals, and other organizations

Powerful tool combs family genomes to find shared variations causing disease

Date:
May 29, 2014
Source:
University of Utah Health Sciences
Summary:
A powerful tool called pVAAST that combines linkage analysis with case control association has been developed to help researchers and clinicians identify disease-causing mutations in families faster and more precisely than ever before. The researchers describe cases in which pVAAST (the pedigree Variant Annotation, Analysis and Search Tool) identified mutations in two families with separate diseases and a de novo or new variation in a 12-year-old who was the only one in his family to suffer from a mysterious and life threatening intestinal problem.

Scientists at the University of Utah (U of U), the University of Texas MD Anderson Cancer Center in Houston and colleagues have developed a powerful tool called pVAAST that combines linkage analysis with case control association to help researchers and clinicians identify disease-causing mutations in families faster and more precisely than ever before.

In a study in Nature Biotechnology, the researchersdescribe cases in which pVAAST (the pedigree Variant Annotation, Analysis and Search Tool) identified mutations in two families with separate diseases and a de novo or new variation in a 12-year-old who was the only one in his family to suffer from a mysterious and life threatening intestinal problem.

"Linkage analysis and case control association traditionally have been used to find gene mutations," says Chad Huff, Ph.D., corresponding author on the study, assistant professor of epidemiology at the MD Anderson Cancer Center and former postdoctoral fellow in human genetics at the U of U. "Bringing those methods together provides a strong increase in the power to find gene variations that cause disease."

The advent of genome sequencing has allowed researchers to search for disease-causing mutations in the genomes of individual patients, larger groups of unrelated people or small and large families. The researchers in this study believe the most powerful way to identify these variants is by sequencing the genomes of families that experience unusually high occurrences of a particular illness. By identifying gene variations that family members share, it's possible to identify mutations in a gene that causes the disease, according to Mark Yandell, Ph.D., U of U professor of human genetics and a senior author on the paper.

"The issue with whole genome sequences has been that sequencing one person's genome to find a single disease-causing gene is difficult," Yandell says. "If you can sequence the whole family it gives a fuller picture of the sequence and variations potentially involved in disease."

Humans carry two healthy copies of each gene in the body. But mutations in a gene can cause disease or other health problems. These mutations occur randomly and rarely, but once they happen in a family member, they are often passed down to subsequent generations.

pVAAST was designed to search the sequenced genomes of families to find shared mutations and thus identify the gene with the highest probability of causing disease. Unlike other gene-finding tools, pVAAST accounts for people being related as it searches for gene variations that have the highest probabilities of causing disease. A big advantage of pVAAST, according to Huff and Yandell, is its ability to simultaneously search multiple families with the same disease to find mutations; this reduces the amount of time and effort to find a disease-causing variant. For example, if three families have the same disease, two might have different mutations damaging the same gene, while the third family might have a different damaged gene. "pVAAST has the power to determine the true disease-causing mutations across all those families in one analysis," Yandell says.

In related work, Yandell, Huff, and their colleagues vastly improved the results of individual and small family sequencing by developing another gene-finding tool, Phevor (Phenotype Driven Variant Ontological Re-ranking tool), which combines the probabilities of mutations being involved with a disease with databases of phenotypes and information on gene functions. In doing this Phevor and pVAAST in combination can identify disease genes with much greater precision than other tools.

Sequencing genomes of unrelated patients with the same disease also increases the ability to find gene variations, and a third software tool Yandell and colleagues developed, VAAST (Variant Annotation, Analysis and Search Tool), has greatly advanced the speed and precision of doing that.

If VAAST or pVAAST can't identify the mutation most likely to cause a disease, Phevor can take the results from those tools and combine them with a description of the patients' disease called a 'phenotype' to find the most likely causative gene.

"We hope that in developing pVAAST, we and other researchers can more rapidly identify genetic variations influencing disease risk by increasing the statistical power of familial genome sequencing," Huff says.


Story Source:

The above story is based on materials provided by University of Utah Health Sciences. Note: Materials may be edited for content and length.


Journal Reference:

  1. Hao Hu, Jared C Roach, Hilary Coon, Stephen L Guthery, Karl V Voelkerding, Rebecca L Margraf, Jacob D Durtschi, Sean V Tavtigian, Shankaracharya, Wilfred Wu, Paul Scheet, Shuoguo Wang, Jinchuan Xing, Gustavo Glusman, Robert Hubley, Hong Li, Vidu Garg, Barry Moore, Leroy Hood, David J Galas, Deepak Srivastava, Martin G Reese, Lynn B Jorde, Mark Yandell, Chad D Huff. A unified test of linkage analysis and rare-variant association for analysis of pedigree sequence data. Nature Biotechnology, 2014; DOI: 10.1038/nbt.2895

Cite This Page:

University of Utah Health Sciences. "Powerful tool combs family genomes to find shared variations causing disease." ScienceDaily. ScienceDaily, 29 May 2014. <www.sciencedaily.com/releases/2014/05/140529182747.htm>.
University of Utah Health Sciences. (2014, May 29). Powerful tool combs family genomes to find shared variations causing disease. ScienceDaily. Retrieved August 23, 2014 from www.sciencedaily.com/releases/2014/05/140529182747.htm
University of Utah Health Sciences. "Powerful tool combs family genomes to find shared variations causing disease." ScienceDaily. www.sciencedaily.com/releases/2014/05/140529182747.htm (accessed August 23, 2014).

Share This




More Health & Medicine News

Saturday, August 23, 2014

Featured Research

from universities, journals, and other organizations


Featured Videos

from AP, Reuters, AFP, and other news services

Drug Used To Treat 'Ebola's Cousin' Shows Promise

Drug Used To Treat 'Ebola's Cousin' Shows Promise

Newsy (Aug. 21, 2014) An experimental drug used to treat Marburg virus in rhesus monkeys could give new insight into a similar treatment for Ebola. Video provided by Newsy
Powered by NewsLook.com
Two US Ebola Patients Leave Hospital Free of the Disease

Two US Ebola Patients Leave Hospital Free of the Disease

AFP (Aug. 21, 2014) Two American missionaries who were sickened with Ebola while working in Liberia and were treated with an experimental drug are doing better and have left the hospital, doctors say on August 21, 2014. Duration: 01:05 Video provided by AFP
Powered by NewsLook.com
Cadavers, a Teen, and a Medical School Dream

Cadavers, a Teen, and a Medical School Dream

AP (Aug. 21, 2014) Contains graphic content. He's only 17. But Johntrell Bowles has wanted to be a doctor from a young age, despite the odds against him. He was recently the youngest participant in a cadaver program at the Indiana University NW medical school. (Aug. 21) Video provided by AP
Powered by NewsLook.com
American Ebola Patients Released: What Cured Them?

American Ebola Patients Released: What Cured Them?

Newsy (Aug. 21, 2014) It's unclear whether the American Ebola patients' recoveries can be attributed to an experimental drug or early detection and good medical care. Video provided by Newsy
Powered by NewsLook.com

Search ScienceDaily

Number of stories in archives: 140,361

Find with keyword(s):
Enter a keyword or phrase to search ScienceDaily for related topics and research stories.

Save/Print:
Share:

Breaking News:
from the past week

In Other News

... from NewsDaily.com

Science News

Health News

Environment News

Technology News



Save/Print:
Share:

Free Subscriptions


Get the latest science news with ScienceDaily's free email newsletters, updated daily and weekly. Or view hourly updated newsfeeds in your RSS reader:

Get Social & Mobile


Keep up to date with the latest news from ScienceDaily via social networks and mobile apps:

Have Feedback?


Tell us what you think of ScienceDaily -- we welcome both positive and negative comments. Have any problems using the site? Questions?
Mobile: iPhone Android Web
Follow: Facebook Twitter Google+
Subscribe: RSS Feeds Email Newsletters
Latest Headlines Health & Medicine Mind & Brain Space & Time Matter & Energy Computers & Math Plants & Animals Earth & Climate Fossils & Ruins