Nano-Dissection Identifies Specific Genes Involved in Kidney Disease

Lisa Zheng
By Lisa Zheng December 23, 2013 23:33

Nano-Dissection Identifies Specific Genes Involved in Kidney Disease

In silico nano-dissection was used to separate and identify genes from diseased kidney cells known as podocytes. Graphic courtesy of Matthias Kretzler.

In silico nano-dissection was used to separate and identify genes from diseased kidney cells known as podocytes. Graphic courtesy of Matthias Kretzler.

The human genome consists of approximately 21,000 genes. Any mixture of mutations of these genes can cause fatal disease in humans. Characterizing genes and how they act is important to the understanding of human disease. However, identification of cell-lineage-specific genes on a genome-wide scale is difficult in most solid human tissues. [1,2] A new method developed by Professor Olga Troyanskaya of Princeton University and Professor Matthias Kretzler of the University of Michigan aims to remedy this. This method is called “in silico nano-dissection,” meaning it uses computers rather than scalpels to separate and identify genes in specific cell types. This technique is unique in that it allows for sections of whole tissue to be examined for genetic signatures associated with specific cell types. [1] It works by evaluating patterns of gene expression under different cell conditions, using this information to deduce what types of cells are present and what genes are expressed and activated in certain cell types. [1]

Compared to normal experimental techniques performed in mice, which are usually only 23% accurate, nano-dissection performed at 65% accuracy in identifying genes related to disease. Graphic courtesy of Altrendo Nature.

Compared to normal experimental techniques performed in mice, which are usually only 23% accurate, nano-dissection performed at 65% accuracy in identifying genes related to disease. Graphic courtesy of Altrendo Nature.

The specific experiment that was done was identifying genes in podocytes in the kidney. Podocytes are known as the “work-horses” of the kidney and are important in the formation of urine. If they malfunction, podocytes may cause kidney disease. It was shown that certain patterns of activity in specific genes can be correlated to the severity of the disease. Compared to techniques used in mice, which were only 23% accurate, the ¬¬in silico nano-dissection method was 65% accurate in determining genes actually related to disease. [1] This accuracy was determined using immunohistochemistry (IHC), which uses antibodies to bind to specific antigens and determine which genes are related to disease. This in silico nano-dissection technique was able to identify 136 genes expressed specifically in podocytes, two of which were shown to be related to glomerular disease in kidneys. [1,2]

In silico nano-dissection was used to identify genes involved in kidney disease and identified two genes that were specifically related to glomerular disease in kidneys. Graphic courtesy of Center for Glomerular Disease at Columbia University.

In silico nano-dissection was used to identify genes involved in kidney disease and identified two genes that were specifically related to glomerular disease in kidneys. Graphic courtesy of Center for Glomerular Disease at Columbia University.

This technique can be used on many other types of tissues, not just kidney-related diseases, suggesting the potential for study of a wide range of diseases and cell physiologies. [1,2] This is a novel technique that opens many new doors for researchers. It could be used to identify cell-type-specific markers which could help perform tests of gene expression. Current next-generation exome sequencing technologies, the part of the genome after introns are removed, often identify multiple candidate genes for hereditary diseases. Thus, this novel method may be a crucial way to help prioritize the candidate genes determined by the exome sequencing. [2]

Sources:
1) http://www.sciencedaily.com/releases/2013/10/131004154808.htm
2) http://genome.cshlp.org/content/early/2013/10/02/gr.155697.113

Lisa Zheng
By Lisa Zheng December 23, 2013 23:33