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UD biologist Salil Lachke has released a new, more powerful
database that could have profound impact on eye research around the
A skilled mechanic who knows every millimeter of an engine always knows which tool to use where and when.
The toolbox biologists and geneticists use, though, has been
expanding - in both scope and precision - rapidly in recent years.
that's a good thing.
Geneticists face many daunting challenges - for
example, how to predict which of the thousands of genes in the human
genome are linked to specific birth defects.
Now, University of Delaware biologist Salil Lachke has released a new power tool - described in a recent Nucleic Acids Research article - that could have profound impact on eye health care for people around the world.
He calls this tool iSyTE 2.0
- pronounced eyesight. The acronym stands for "integrated Systems
Tool for Eye gene discovery." The program builds on the original
But comparing 1.0 to 2.0 is a bit like comparing a 10-speed bicycle
to a Kawasaki Ninja motorcycle. The zoom factor (not a scientific term)
has gone way up.
"There is a national database called GEO [Geo Expression Omnibus]
from which anyone can download thousands of 'raw' tissue-specific gene
expression datasets," Lachke said. "But as they are, these raw data are
not very useful because most folks don't have the skillsets to analyze
and effectively visualize it to get maximum mileage from it."
The new iSyTE 2.0 database web-resource addresses just that. The
website, hosted at UD's Center for Bioinformatics and Computational
Biology and supported by grants from the National Eye Institute at the
National Institutes of Health and the Pew Charitable Trusts Biomedical
Sciences Scholarship, provides not only far more ready-to-use data, but
also powerful ways to customize the information, curated and categorized
to allow user-specified analysis on several layers simultaneously.
"We built a brand new website for biologists or for that matter
really anybody to access the fully processed eye expression data," he
said. "Which stage of lens development do you want to look at? Which
specific gene mutant? All this information is now at your fingertips."
Not that 1.0 was a slouch. That early version of this tool led to
several key advances, for example the identification - in Lachke's lab -
of regulatory factors (Mafg, Mafk, Caprin2 and others) that are
necessary for normal lens development and has expedited gene discovery
in cataract research.
These bioinformatics tools help researchers sort through genes to find those with strong links to eye disorders and defects.
"It is a game-changer," Lachke said.
Data are drawn from many labs and carefully curated. Less than 5 percent has been "outlier" data - not useable, he said.
The idea for this power tool simmered in Lachke's imagination for
more than a decade, first during his postdoctoral years and then as a
member of UD's faculty.
"The technology was getting there," he said, "but the scientific
cultural aspect of using big data sets was still evolving - even now it
is still evolving. Now, by using such genome-level eye tissue expression
datasets, we can make specific predictions about the about which genes -
from about 20,000 protein-coding genes in the human genome - are linked
to eye diseases and systematically test those predictions in the
Next on Lachke's radar - iSyTE version 3.0, with even more detailed RNA sequencing-based data of the lens, cornea and retina.
Lachke dreams of developing similar tools specific to other organs
and tissues in the future and already has one in the making for
craniofacial defects, which are among the most common human
Some have asked if he is concerned about someone "scooping" his research.
"On the contrary," he said, "involving more scientists is precisely
the point. My five-year budget is about $2 million. Yet even with that
we cannot work on everything we have found to be novel.
"Bring it on. Open it up. There is so much data out there and with
the kind of challenges we face with human developmental defects, one
scientist cannot do it all in a lifetime.
"Plus, different people often take different views on the same
datasets, maximizing their utility - and that is good for science."
The work is dedicated to the memory of David Beebe, professor of
ophthalmology and visual sciences at Washington University and a mentor
of high significance to Lachke.
Other contributors include UD's Atul Kakrana, Deepti Anand, Deepti
Ramachandruni, Abhyudai Singh and Hongzhan Huang, along with Andrian
Yang, Djordje Djordjevic and Joshua Ho of the Victor Chang Cardiac
Research Institute in Australia.
Salil Lachke is an associate professor of biological sciences at the
University of Delaware, focusing on genetic research related to organ
development and disease, especially in the eye. He earned his bachelor's
and master's degrees at the University of Pune, India, his doctorate at
the University of Iowa and did postdoctoral work at Harvard Medical
School, where he also served as an instructor. He joined the University
of Delaware faculty in 2011. His innovative research has won many awards
and he is a Gerard J. Mangone Scholar and a Pew Scholar in the
Article by Beth Miller; photo illustration by Jeffrey Chase
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