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n2doc

(47,953 posts)
Fri Nov 8, 2013, 01:35 PM Nov 2013

Surprising Variation Among Genomes of Individual Neurons from Same Brain

It was once thought that each cell in a person's body possesses the same DNA code and that the particular way the genome is read imparts cell function and defines the individual. For many cell types in our bodies, however, that is an oversimplification. Studies of neuronal genomes published in the past decade have turned up extra or missing chromosomes, or pieces of DNA that can copy and paste themselves throughout the genomes.

The only way to know for sure that neurons from the same person harbor unique DNA is by profiling the genomes of single cells instead of bulk cell populations, the latter of which produce an average. Now, using single-cell sequencing, Salk Institute researchers and their collaborators have shown that the genomic structures of individual neurons differ from each other even more than expected. The findings were published November 1 in Science.

"Contrary to what we once thought, the genetic makeup of neurons in the brain aren't identical, but are made up of a patchwork of DNA," says corresponding author Fred Gage, Salk's Vi and John Adler Chair for Research on Age-Related Neurodegenerative Disease.

In the study, led by Mike McConnell, a former junior fellow in the Crick-Jacobs Center for Theoretical and Computational Biology at the Salk, researchers isolated about 100 neurons from three people posthumously. The scientists took a high-level view of the entire genome -- -- looking for large deletions and duplications of DNA called copy number variations or CNVs -- -- and found that as many as 41 percent of neurons had at least one unique, massive CNV that arose spontaneously, meaning it wasn't passed down from a parent. The CNVs are spread throughout the genome, the team found.

The miniscule amount of DNA in a single cell has to be chemically amplified many times before it can be sequenced. This process is technically challenging, so the team spent a year ruling out potential sources of error in the process.

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http://www.sciencedaily.com/releases/2013/11/131101172313.htm

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