What has been the growth rate of computing power, multi-neuron recording, and DNA sequencing over the past decade? Konrad Kording provides an illuminating chart pertaining to this question:
neurons recorded = the number of neurons that can be recorded from simultaneously; the neuron and computer scales are exponential fits to data; doi:10.1371/journal.pcbi.1002291
Given the above DNA sequencing trends, it’s no surprise that groups in many different fields are developing strategies to turn the problem they are trying to study into a sequencing problem.
See, for example, Jonathan Weissman’s talk on ribosome profiling, which is an elegant way to use DNA sequencing of mRNA molecules tethered to the ribosome as a way to study translation.
In his article, Kording touches on a couple of intriguing sequencing technologies that might help make the “data-out” step of a given neuroscience experiment more high-throughput.
The method for connectomics he describes is particularly fascinating. The idea is to assign neurons a unique DNA barcode that is spread to each of its synaptic partners via a transsynaptic virus, and then sequence the set of barcodes from a given group of cells.
One aspect that I think Kording might have underemphasized is that these technologies would improve greatly if we improved our ability to sequence the DNA of individual neurons.
For example, typical protocols for probing the expression of intermediate early genes rely on harvesting cells from mass culture or coarse brain regions before sequencing. This is powerful, but it would be much more so if we could analyze the distribution of gene expression between cells rather than across them.
Single-cell genomics is advancing, but it is not yet at the point of routine laboratory use for a typical sequencing experiment. And in order to really take advantage of DNA sequencing technology in understanding how networks of neurons work together, it will presumably need to reach that point.
References
Kording KP (2011) Of Toasters and Molecular Ticker Tapes. PLoS Comput Biol 7(12): e1002291. doi:10.1371/journal.pcbi.1002291
Link to Jonathan Weissman’s 11/16/11 talk.
Oyibo H, et al. 2011 Probing the connectivity of neural circuits at single-neuron resolution using high-throughput DNA sequencing. Presentation at Computational and Systems Neuroscience Meeeting, pdf.
Saha RN, et al. 2011 Rapid activity-induced transcription of arc and other IEGs relies on poised RNA polymerase II. doi: 10.1038/nn.2839.
Kalisky T, et al. 2011 Single-cell genomics. doi:10.1038/nmeth0411-311
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