A shift in the code: New method reveals hidden genetic landscape

The letters in the human genome carry instructions to make proteins, via a three-letter code. Each trio spells out a word, and the words are strung together in a sentence to build a specific protein. Inserting or deleting a letter ('e' in this example) shifts the three-letter code. Known as a frameshift, these mutations cause the remaining words to be misspelled and the protein sentence to become unintelligible. Credit: J. Jansen/ Cold Spring Harbor Laboratory

With three billion letters in the human genome, it seems hard to believe that adding a DNA base here or removing a DNA base there could have much of an effect on our health. In fact, such insertions and deletions can dramatically alter biological function, leading to diseases from autism to cancer.

Still, it is has been difficult to detect these mutations. Now, a team of scientists at Cold Spring Harbor Laboratory (CSHL) has devised a new way to analyze genome sequences that pinpoints so-called insertion and deletion mutations (known as “indels”) in genomes of people with diseases such as autism, obsessive-compulsive disorder and Tourette syndrome.

The letters in the human genome carry instructions to make proteins, via a three-letter code. Each trio spells out a “word;” the words are then strung together in a sentence to build a specific protein. If a letter is accidentally inserted or deleted from our genome, the three-letter code shifts a notch, causing all of the subsequent words to be misspelled.

These “frameshift” mutations cause the protein sentence to become unintelligible. Loss of a single protein can have devastating effects for cells, leading to dysfunction and sometimes to serious diseases.

DNA insertions and deletions vary in length and sequence. Each indel can range in size from one DNA letter to thousands, and they are often highly repetitive. Their variability has made it challenging to identify indels, despite major advancements in genome sequencing technology. They are, in effect, regions of the genome that have remained hidden from view as researchers search for the mutations that cause disease.

A team of CSHL scientists, including Assistant Professors Mike Schatz, Gholson Lyon, and Ivan Iossifov, and Professor Michael Wigler, has devised a way to mine existing genomic datasets for indel mutations. The method, which they call Scalpel, begins by grouping together all of the sequences from a given genomic region. Scalpel – a computer formula, or algorithm – then creates a new sequence alignment for that area, much like piecing together parts of a puzzle.

“These indels are like very fine cuts to the genome – places where DNA is inserted or deleted – and Scalpel provides us with a computational lens to zoom in and see precisely where the cuts occur,” says Schatz, a quantitative biologist. Such information is critical to understand the mutations that cause disease.

In work published today in Nature Methods, the team used Scalpel to search for indels in patient samples. Lyon, a CSHL researcher who is also a practicing psychiatrist, worked with his team to analyze a patient with severe Tourette syndrome and obsessive-compulsive disorder, identifying and validating more than a thousand indels to demonstrate the accuracy of the method.

The CSHL team performed a similar analysis to search for indels that are associated with autism. They explored a dataset of 593 families from the Simons Simplex Collection, a group composed entirely of families with one affected child but no other family members with the disorder. While the researchers discovered a total of 3.3 million indels across the 593 families, most appeared to be relatively harmless. Still, a few dozen mutations stood out to be specifically associated with autism. “All this adds to our body of knowledge about the spontaneous mutations that cause autism,” says Schatz.

But the tool can be applied much more broadly. “We are collaborating with plant scientists, cancer biologists, and others, looking for indels,” says Schatz. “This is a powerful tool, and we are looking forward to revealing new pieces of the genome that make a difference, throughout the tree of life.”

###

This work was supported by US National Institutes of Health, US National Science Foundation, the CSHL Cancer Center Support Grant, the Stanley Institute for Cognitive Genomics, and the Simons Foundation.

“Accurate de novo and transmitted indel detection in exome-capture data using microassembly” appears online in Nature Methods on August 17, 2014. The authors are: Giuseppe Narzisi, Jason O'Rawe, Ivan Iossifov, Han Fang, Yoon-ha Lee, Zihua Wang, Yiyang Wu, Gholson Lyon, Michael Wigler, and Michael Schatz.

The paper can be obtained online at: http://dx.doi.org/10.1038/nmeth.3069

About Cold Spring Harbor Laboratory

Founded in 1890, Cold Spring Harbor Laboratory (CSHL) has shaped contemporary biomedical research and education with programs in cancer, neuroscience, plant biology and quantitative biology. CSHL is ranked number one in the world by Thomson Reuters for the impact of its research in molecular biology and genetics. The Laboratory has been home to eight Nobel Prize winners. Today, CSHL's multidisciplinary scientific community is more than 600 researchers and technicians strong and its Meetings & Courses program hosts more than 12,000 scientists from around the world each year to its Long Island campus and its China center. For more information, visit http://www.cshl.edu

Media Contact

Jaclyn Jansen Eurek Alert!

All latest news from the category: Life Sciences and Chemistry

Articles and reports from the Life Sciences and chemistry area deal with applied and basic research into modern biology, chemistry and human medicine.

Valuable information can be found on a range of life sciences fields including bacteriology, biochemistry, bionics, bioinformatics, biophysics, biotechnology, genetics, geobotany, human biology, marine biology, microbiology, molecular biology, cellular biology, zoology, bioinorganic chemistry, microchemistry and environmental chemistry.

Back to home

Comments (0)

Write a comment

Newest articles

Machine learning algorithm reveals long-theorized glass phase in crystal

Scientists have found evidence of an elusive, glassy phase of matter that emerges when a crystal’s perfect internal pattern is disrupted. X-ray technology and machine learning converge to shed light…

Mapping plant functional diversity from space

HKU ecologists revolutionize ecosystem monitoring with novel field-satellite integration. An international team of researchers, led by Professor Jin WU from the School of Biological Sciences at The University of Hong…

Inverters with constant full load capability

…enable an increase in the performance of electric drives. Overheating components significantly limit the performance of drivetrains in electric vehicles. Inverters in particular are subject to a high thermal load,…

Partners & Sponsors