New genetic analysis method could advance personal genomics
Computational method capable of decoding influence of rare variants

Date:
September 10, 2020
Source:
Johns Hopkins University
Summary:
Geneticists could identify the causes of disorders that currently
go undiagnosed if standard practices for collecting individual
genetic information were expanded to capture more variants that
researchers can now decipher, concludes new research.



FULL STORY ========================================================================== Geneticists could identify the causes of disorders that currently go undiagnosed if standard practices for collecting individual genetic
information were expanded to capture more variants that researchers can
now decipher, concludes new Johns Hopkins University research.


==========================================================================
The laboratory of Johns Hopkins biomedical engineering professor
Alexis Battle has developed a technique to begin identifying potentially problematic rare genetic variants that exist in the genomes of all people, particularly if additional genetic sequencing information was included
in standard collection methods. The team's findings are published in the
latest issue of Science and are part of the Genotype-Tissue Expression
(GTEx) Program funded by the National Institutes of Health.

"The implications of this could be quite large. Everyone has around
50,000 variants that are rare in the population and we have absolutely
no idea what most of them are doing," Battle said. "If you collect gene expression data, which shows which proteins are being produced in a
patient's cells at what levels, we're going to be able to identify what's
going on at a much higher rate." While approximately 8% of U.S. citizens, mostly children, suffer from genetic disorders, the genetic cause has
not been found for about half of the cases.

What's even more frustrating, according to Battle, is that even more
people are likely living with more subtle genetically-influenced health ailments that have not been identified.

"We really don't know how many people are out there walking around with a genetic aberration that is causing them health issues," she said. "They
go completely undiagnosed, meaning we cannot find the genetic cause
of their problems." The field of personalized genomics is unable
to characterize these rare variants because most genetic variants,
specifically variants that are in "non- coding" parts of the genome that
do not specify a protein, are not tested.

Doing so would represent a major advance in a growing field that is
focused on the sequencing and analysis of individuals' genomes, she said.

The Battle Lab developed a computational system called "Watershed" that
can scour reams of genetic data along with gene expression to predict
the functions of variants from individual's genomes. They validated
those predictions in the lab and applied the findings to assess the rare variants captured in massive gene collections such as the UK Biobank,
the Million Veterans Program and the Jackson Heart Study. The results
have helped to show which rare variants may be impacting human traits.

"Any improvement we can make in this area has implications for public
health," Battle said. "Even pointing to what the genetic cause is gives
parents and patients a huge sense of relief and understanding and can
point to potential therapeutics."

========================================================================== Story Source: Materials provided by Johns_Hopkins_University. Note:
Content may be edited for style and length.


========================================================================== Journal Reference:
1. Nicole M. Ferraro, Benjamin J. Strober, Jonah Einson, Nathan
S. Abell,
Francois Aguet, Alvaro N. Barbeira, Margot Brandt, Maja Bucan,
Stephane E. Castel, Joe R. Davis, Emily Greenwald, Gaelen T. Hess,
Austin T.

Hilliard, Rachel L. Kember, Bence Kotis, YoSon Park, Gina Peloso,
Shweta Ramdas, Alexandra J. Scott, Craig Smail, Emily K. Tsang,
Seyedeh M.

Zekavat, Marcello Ziosi, Aradhana, Kristin G. Ardlie, Themistocles
L.

Assimes, Michael C. Bassik, Christopher D. Brown, Adolfo Correa,
Ira Hall, Hae Kyung Im, Xin Li, Pradeep Natarajan, Tuuli
Lappalainen, Pejman Mohammadi, Stephen B. Montgomery, Alexis
Battle. Transcriptomic signatures across human tissues identify
functional rare genetic variation. Science, 2020; 369 (6509):
eaaz5900 DOI: 10.1126/ science.aaz5900 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2020/09/200910150302.htm

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