Featured Research

from universities, journals, and other organizations

Nano-dissection identifies genes involved in kidney disease

Date:
October 4, 2013
Source:
Princeton University
Summary:
A new method developed by researchers called "in silico nano-dissection" uses computers rather than scalpels to separate and identify genes from specific cell types, enabling the systematic study of genes involved in diseases.

Researchers at Princeton and the University of Michigan have created a computer-based method for separating and identifying genes from diseased kidney cells known as podocytes, pictured above.
Credit: Image courtesy of Matthias Kretzler

Understanding how genes act in specific tissues is critical to our ability to combat many human diseases, from heart disease to kidney failure to cancer. Yet isolating individual cell types for study is impossible for most human tissues.

A new method developed by researchers at Princeton University and the University of Michigan called "in silico nano-dissection" uses computers rather than scalpels to separate and identify genes from specific cell types, enabling the systematic study of genes involved in diseases.

The team used the new method to successfully identify genes expressed in cells known as podocytes -- the "work-horses" of the kidney -- that malfunction in kidney disease. The investigators showed that certain patterns of activity of these genes were correlated with the severity of kidney impairment in patients, and that the computer-based approach was significantly more accurate than existing experimental methods in mice at identifying cell-lineage-specific genes. The study was published in the journal Genome Research.

Using this technique, researchers can now examine the genes from a section of whole tissue, such as a biopsied section of the kidney, for specific signatures associated with certain cell types. By evaluating patterns of gene expression under different conditions in these cells, a computer can use machine-learning techniques to deduce which types of cells are present. The system can then identify which genes are expressed in the cell type in which they are interested. This information is critical both in defining novel disease biomarkers and in selecting potential new drug targets.

By applying the new method to kidney biopsy samples, the researchers identified at least 136 genes as expressed specifically in podocytes. Two of these genes were experimentally shown to be able to cause kidney disease. The authors also demonstrated that in silico nano-dissection can be used for cells other than those found in the kidney, suggesting that the method is useful for the study of a range of diseases.

The computational method was significantly more accurate than another commonly used technique that involves isolating specific cell types in mice. The nano-dissection method's accuracy was 65% versus 23% for the mouse method, as evaluated by a time-consuming process known as immunohistochemistry which involves staining each gene of interest to study its expression pattern.

The research was co-led by Olga Troyanskaya, a professor of computer science and the Lewis-Sigler Institute for Integrative Genomics at Princeton, and Matthias Kretzler, a professor of computational medicine and biology at the University of Michigan. The first authors on the study were Wenjun Ju, a research assistant professor at the University of Michigan, and Casey Greene, now at the Geisel School of Medicine at Dartmouth and a former postdoctoral fellow at Princeton.


Story Source:

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


Journal Reference:

  1. W. Ju, C. S. Greene, F. Eichinger, V. Nair, J. B. Hodgin, M. Bitzer, Y.-s. Lee, Q. Zhu, M. Kehata, M. Li, S. Jiang, M. P. Rastaldi, C. D. Cohen, O. G. Troyanskaya, M. Kretzler. Defining cell-type specificity at the transcriptional level in human disease. Genome Research, 2013; DOI: 10.1101/gr.155697.113

Cite This Page:

Princeton University. "Nano-dissection identifies genes involved in kidney disease." ScienceDaily. ScienceDaily, 4 October 2013. <www.sciencedaily.com/releases/2013/10/131004154808.htm>.
Princeton University. (2013, October 4). Nano-dissection identifies genes involved in kidney disease. ScienceDaily. Retrieved July 31, 2014 from www.sciencedaily.com/releases/2013/10/131004154808.htm
Princeton University. "Nano-dissection identifies genes involved in kidney disease." ScienceDaily. www.sciencedaily.com/releases/2013/10/131004154808.htm (accessed July 31, 2014).

Share This




More Health & Medicine News

Thursday, July 31, 2014

Featured Research

from universities, journals, and other organizations


Featured Videos

from AP, Reuters, AFP, and other news services

Health Insurers' Profits Slide

Health Insurers' Profits Slide

Reuters - Business Video Online (July 30, 2014) Obamacare-related costs were said to be behind the profit plunge at Wellpoint and Humana, but Wellpoint sees the new exchanges boosting its earnings for the full year. Fred Katayama reports. Video provided by Reuters
Powered by NewsLook.com
Concern Grows Over Worsening Ebola Crisis

Concern Grows Over Worsening Ebola Crisis

AFP (July 30, 2014) Pan-African airline ASKY has suspended all flights to and from the capitals of Liberia and Sierra Leone amid the worsening Ebola health crisis, which has so far caused 672 deaths in Guinea, Liberia and Sierra Leone. Duration: 00:43 Video provided by AFP
Powered by NewsLook.com
At Least 20 Chikungunya Cases in New Jersey

At Least 20 Chikungunya Cases in New Jersey

AP (July 30, 2014) At least 20 New Jersey residents have tested positive for chikungunya, a mosquito-borne virus that has spread through the Caribbean. (July 30) Video provided by AP
Powered by NewsLook.com
Xtreme Eating: Your Daily Caloric Intake All On One Plate

Xtreme Eating: Your Daily Caloric Intake All On One Plate

Newsy (July 30, 2014) The Center for Science in the Public Interest released its 2014 list of single meals with whopping calorie counts. 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