2026-09-20T16:59:49Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1392072022-01-15T03:48:24Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Boyden, Edward S.
Romero, Cipriano William
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2022-01-14T14:56:41Z
2022-01-14T14:56:41Z
2021-06
2021-06-24T19:39:25.688Z
https://hdl.handle.net/1721.1/139207
In this work, we explore the intersection of in situ sequencing, neural recording, and CRISPR screens. An intracellular technology is outlined for encoding neural activity in the form of RNA, theoretically enabling single-cell resolution recording of whole-brain activity. This neural recording system can be coupled with perturb-seq in order to observe high-throughput genetic perturbations of neurons with both temporal and transcriptomic information. Untargeted expansion sequencing (ExSeq) can be used to generate a high-resolution spatiotemporal dataset that includes single guide RNAs (sgRNAs), neural activity, and transcriptomics. Targeted ExSeq, with the inclusion of no-gap padlock probes and SplintR ligase, can be applied to enhance the detection of sgRNA barcodes and targeted transcripts. In vitro and in vivo experimental pipelines are proposed for the fusion of these technologies, in this theoretical thesis.
S.M.
Massachusetts Institute of Technology
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https://rightsstatements.org/page/InC-EDU/1.0/
In Situ Perturb-Seq of Transcriptomes and RNA Neural Recordings
Thesis
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Master
Master of Science in Electrical Engineering and Computer Science
Publication
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<Abstract>In this work, we explore the intersection of in situ sequencing, neural recording, and CRISPR screens. An intracellular technology is outlined for encoding neural activity in the form of RNA, theoretically enabling single-cell resolution recording of whole-brain activity. This neural recording system can be coupled with perturb-seq in order to observe high-throughput genetic perturbations of neurons with both temporal and transcriptomic information. Untargeted expansion sequencing (ExSeq) can be used to generate a high-resolution spatiotemporal dataset that includes single guide RNAs (sgRNAs), neural activity, and transcriptomics. Targeted ExSeq, with the inclusion of no-gap padlock probes and SplintR ligase, can be applied to enhance the detection of sgRNA barcodes and targeted transcripts. In vitro and in vivo experimental pipelines are proposed for the fusion of these technologies, in this theoretical thesis.</Abstract>
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