Literature DB >> 33237042

Enabling high-throughput single-animal gene-expression studies with molecular and micro-scale technologies.

Jason Wan1, Hang Lu2.   

Abstract

Gene expression and regulation play diverse and important roles across all living systems. By quantifying the expression, whether in a sample of single cells, a specific tissue, or in a whole animal, one can gain insights into the underlying biology. Many biological questions now require single-animal and tissue-specific resolution, such as why individuals, even within an isogenic population, have variations in development and aging across different tissues and organs. The popular techniques that quantify the transcriptome (e.g. RNA-sequencing) process populations of animals and cells together and thus, have limitations in both individual and spatial resolution. There are single-animal assays available (e.g. fluorescent reporters); however, they suffer other technical bottlenecks, such as a lack of robust sample-handling methods. Microfluidic technologies have demonstrated various improvements throughout the years, and it is likely they can enhance the impact of these single-animal gene-expression assays. In this perspective, we aim to highlight how the engineering/method-development field have unique opportunities to create new tools that can enable us to robustly answer the next set of important questions in biology that require high-density, high-quality gene expression data.

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Year:  2020        PMID: 33237042      PMCID: PMC7769683          DOI: 10.1039/d0lc00881h

Source DB:  PubMed          Journal:  Lab Chip        ISSN: 1473-0189            Impact factor:   6.799


  102 in total

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Journal:  Nature       Date:  2010-03-25       Impact factor: 49.962

2.  Caloric Restriction Reprograms the Single-Cell Transcriptional Landscape of Rattus Norvegicus Aging.

Authors:  Shuai Ma; Shuhui Sun; Lingling Geng; Moshi Song; Wei Wang; Yanxia Ye; Qianzhao Ji; Zhiran Zou; Si Wang; Xiaojuan He; Wei Li; Concepcion Rodriguez Esteban; Xiao Long; Guoji Guo; Piu Chan; Qi Zhou; Juan Carlos Izpisua Belmonte; Weiqi Zhang; Jing Qu; Guang-Hui Liu
Journal:  Cell       Date:  2020-02-26       Impact factor: 41.582

3.  A simple culture system for long-term imaging of individual C. elegans.

Authors:  William E Pittman; Drew B Sinha; William B Zhang; Holly E Kinser; Zachary Pincus
Journal:  Lab Chip       Date:  2017-11-07       Impact factor: 6.799

4.  An integrated hybrid microfluidic device for oviposition-based chemical screening of adult Drosophila melanogaster.

Authors:  Jacob C K Leung; Arthur J Hilliker; Pouya Rezai
Journal:  Lab Chip       Date:  2016-01-15       Impact factor: 6.799

5.  From single-cell to cell-pool transcriptomes: stochasticity in gene expression and RNA splicing.

Authors:  Georgi K Marinov; Brian A Williams; Ken McCue; Gary P Schroth; Jason Gertz; Richard M Myers; Barbara J Wold
Journal:  Genome Res       Date:  2013-12-03       Impact factor: 9.043

6.  Neuronal Small RNAs Control Behavior Transgenerationally.

Authors:  Rachel Posner; Itai Antoine Toker; Olga Antonova; Ekaterina Star; Sarit Anava; Eran Azmon; Michael Hendricks; Shahar Bracha; Hila Gingold; Oded Rechavi
Journal:  Cell       Date:  2019-06-06       Impact factor: 41.582

7.  Developmental ROS individualizes organismal stress resistance and lifespan.

Authors:  Daphne Bazopoulou; Daniela Knoefler; Yongxin Zheng; Kathrin Ulrich; Bryndon J Oleson; Lihan Xie; Minwook Kim; Anke Kaufmann; Young-Tae Lee; Yali Dou; Yong Chen; Shu Quan; Ursula Jakob
Journal:  Nature       Date:  2019-12-04       Impact factor: 49.962

8.  Specific age-related signatures in Drosophila body parts transcriptome.

Authors:  Fabrice Girardot; Christelle Lasbleiz; Véronique Monnier; Hervé Tricoire
Journal:  BMC Genomics       Date:  2006-04-04       Impact factor: 3.969

9.  Single-molecule RNA detection at depth by hybridization chain reaction and tissue hydrogel embedding and clearing.

Authors:  Sheel Shah; Eric Lubeck; Maayan Schwarzkopf; Ting-Fang He; Alon Greenbaum; Chang Ho Sohn; Antti Lignell; Harry M T Choi; Viviana Gradinaru; Niles A Pierce; Long Cai
Journal:  Development       Date:  2016-06-24       Impact factor: 6.868

10.  Single-cell RNA sequencing reveals intrinsic and extrinsic regulatory heterogeneity in yeast responding to stress.

Authors:  Audrey P Gasch; Feiqiao Brian Yu; James Hose; Leah E Escalante; Mike Place; Rhonda Bacher; Jad Kanbar; Doina Ciobanu; Laura Sandor; Igor V Grigoriev; Christina Kendziorski; Stephen R Quake; Megan N McClean
Journal:  PLoS Biol       Date:  2017-12-14       Impact factor: 8.029

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