Genomics and Applied Biology 2024, Vol.15, No.1, 39-46 http://bioscipublisher.com/index.php/gab 45 Looking ahead, the application prospects of single-cell genomics in neuroscience research will be even broader. With continuous innovation and optimization of the technology, we can expect the emergence of more precise and efficient single-cell genomics techniques. These technologies will provide the possibility to reveal more secrets of the nervous system, thereby promoting the deep development of neuroscience research. Meanwhile, with the continuous accumulation of single-cell genomics data, effectively integrating, analyzing, and interpreting this data will become a focus of research. This will require us to invest more effort in data processing and analysis to unearth more biological information. Furthermore, as single-cell genomics continues to evolve, it is expected to be applied in more areas of neuroscience research, such as neurodevelopment, neuroplasticity, and neuroimmunity. This will provide possibilities to reveal more aspects of the nervous system, thereby promoting the comprehensive development of neuroscience research. Reference Abraham V.G., Yang Y.Y., Amay J.B., and John A.R., 2020, Recent advances in neurotechnologies with broad potential for neuroscience research, Nature Neuroscience, 23: 1522-1536. https://doi.org/10.1038/s41593-020-00739-8 Aqrawe Z., Montgomery J., Travas-Sejdic J., and Svirskis D., 2018, Conducting polymers for neuronal microelectrode array recording and stimulation, Sens. Actuators B Chem., 257: 753-765. https://doi.org/10.1016/j.snb.2017.11.023 Cadwell C.R., Scala F., Li S., Livrizzi G., Shen S., and Sandberg R., 2017, Multimodal profiling of single-cell morphology, electrophysiology, and gene expression using Patch-seq, Nat. Protoc., 12: 2531-2553. https://doi.org/10.1038/nprot.2017.120 Clark S.J., Argelaguet R., Kapourani C.A., Stubbs T.M., Lee H.J., and Alda-Catalinas C., 2018, scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells, Nat. Commun, 9: 781. https://doi.org/10.1038/s41467-018-03149-4 Hu Y.J., An Q., Sheu K., Trejo B., Fan S.X., and Guo Y., 2018, Single cell multi-omics technology: Methodology and application, Front. Cell Dev. Biol., 6. https://doi.org/10.3389/fcell.2018.00028 Jeongwoo L., Do Y.H., and Daehee H., 2020, Single-cell multiomics: technologies and data analysis methods, Experimental & Molecular Medicine, 52: 1428-1442. https://doi.org/10.1038/s12276-020-0420-2 Leopold A.V., Shcherbakova D.M., and Verkhusha V.V., 2019, Fluorescent biosensors for neurotransmission and neuromodulation: Engineering and applications, Front. Cell. Neurosci., 13: 474. https://doi.org/10.3389/fncel.2019.00474 Lia C., Andrew J.C., and Thierry V., 2018, Single-cell (Multi) omics technologies, Annual Review of Genomics and Human Genetics, 19: 15-41. https://doi.org/10.1146/annurev-genom-091416-035324 Lin P., Troup M., and Ho J.W., 2017, CIDR: ultrafast and accurate clustering through imputation for single-cell RNA-seq data, Genome Biol., 18: 59. https://doi.org/10.1186/s13059-017-1188-0 Lu W., and Tang F.C., 2022, Recent advances in single-cell sequencing technologies, Precision Clinical Medicine, 5: 1. https://doi.org/10.1093/pcmedi/pbac002 Musk E., 2019, An integrated brain-machine interface platform with thousands of channels, J. Med. Internet Res., 21: e16194. https://doi.org/10.2196/16194 O’Banion C.P., and Yasuda R., 2020, Fluorescent sensors for neuronal signaling, Curr. Opin. Neurobiol., 63: 31-41. https://doi.org/10.1016/j.conb.2020.02.007 Rochford A.E., Carnicer-Lombarte A., Curto V.F., Malliaras G.G. and Barone D.G., 2020, When bio meets technology: Biohybrid neural interfaces, Adv. Mater., 32: e1903182. https://doi.org/10.1002/adma.201903182 Shen Y., Nasu Y., Shkolnikov I., Kim A. and Campbell R.E., 2020, Engineering genetically encoded fluorescent indicators for imaging of neuronal activity: progress and prospects, Neurosci. Res., 152: 3-14. https://doi.org/10.1016/j.neures.2020.01.011 Song E., Li J., Won S.M., Bai W., and Rogers J.A., 2020, Materials for flexible bioelectronic systems as chronic neural interfaces, Nat. Mater., 19: 590-603. https://doi.org/10.1038/s41563-020-0679-7 Tavakolian-Ardakani Z., Hosu O., Cristea C., Mazloum-Ardakani M., and Marrazza G., 2019, Latest trends in electrochemical sensors for neurotransmitters: a review, Sensors (Basel), 19: 2037. https://doi.org/10.3390/s19092037
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