Using high-throughput barcode sequencing to efficiently map connectomes
Author(s) -
Ian D. Peikon,
Justus M. Kebschull,
Vasily V. Vagin,
Diana I. Ravens,
Yu-Chi Sun,
Eric Brouzés,
Ivan R. Corrêa,
Dario Bressan,
Anthony M. Zador
Publication year - 2017
Publication title -
nucleic acids research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.008
H-Index - 537
eISSN - 1362-4954
pISSN - 0305-1048
DOI - 10.1093/nar/gkx292
Subject(s) - barcode , connectome , biology , synapse , computational biology , wiring diagram , tracing , dna sequencing , massively parallel , postsynaptic potential , computer science , neuroscience , dna , genetics , parallel computing , functional connectivity , engineering , receptor , electrical engineering , operating system
The function of a neural circuit is determined by the details of its synaptic connections. At present, the only available method for determining a neural wiring diagram with single synapse precision-a 'connectome'-is based on imaging methods that are slow, labor-intensive and expensive. Here, we present SYNseq, a method for converting the connectome into a form that can exploit the speed and low cost of modern high-throughput DNA sequencing. In SYNseq, each neuron is labeled with a unique random nucleotide sequence-an RNA 'barcode'-which is targeted to the synapse using engineered proteins. Barcodes in pre- and postsynaptic neurons are then associated through protein-protein crosslinking across the synapse, extracted from the tissue, and joined into a form suitable for sequencing. Although our failure to develop an efficient barcode joining scheme precludes the widespread application of this approach, we expect that with further development SYNseq will enable tracing of complex circuits at high speed and low cost.
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