Research Progress of Spatiotemporal Transcriptomes

doi:10.11983/CBB22220

Abstract

Abstract: Spatiotemporal heterogeneity is a key factor for functional differentiation in different tissues and plays an important role in regulating cell fate. Spatiotemporal transcriptomic sequencing (stRNA-seq) is an emerging omics technology that combines quantitative transcriptome with high-resolution tissue imaging. It anchors expression data to the physical map of a target organ or tissue and molecularly characterizes tissue sections and cell layers via unbiased bioinformatic analysis, which reflects the spatiotemporal heterogeneity of gene expression abundances within specific cells. Benefiting from the rapid development of high-throughput sequencing, the spatiotemporal heterogeneity of gene expression in various cells can be explored by new experimental approaches. In this review, we first briefly introduce the principle and development process of stRNA-seq, providing readers an overview on the characteristics, advantages and disadvantages of different stRNA-seq techniques. Then, we summarize the applications of stRNA-seq in animals, plants and microorganisms, which provide theoretical references for the systematic research of stRNA-seq in future.

Key words: spatiotemporal transcriptomics, spatial and temporal heterogeneity, single cell

Yubin Xiao, Zixu Zhang, Yuzhu Wang, Huan Liu, Letian Chen. Research Progress of Spatiotemporal Transcriptomes[J]. Chinese Bulletin of Botany, 2023, 58(2): 214-232.

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URL: https://www.chinbullbotany.com/EN/10.11983/CBB22220

https://www.chinbullbotany.com/EN/Y2023/V58/I2/214

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References 105

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	动物	植物
特有结构	?	细胞壁(初生壁和次生壁)、液泡和叶绿体
包埋方法	冷冻包埋和石蜡包埋	冷冻包埋
组织切片	相对简单	相对困难, 高度木质化组织容易开裂、液泡易产生结晶等
染色方法	苏木精-伊红染色和ssDNA染色	甲苯铵蓝染色、ssDNA染色和钙白染色
组织透化	透化细胞膜	透化细胞壁和细胞膜, 且不同植物细胞的细胞壁成分存在较大异质性
组织移除	相对简单	高度成熟组织的降解可能需要较长的时间和苛刻的组织移除操作, 可能会影响逆转录产物
参考基因组	参考基因组较为完善	参考基因组有待进一步完善
技术平台	大量时空组技术优先适配于动物组织	时空组技术在植物组织中的应用条件仍有待进一步优化
时空组学文献数量	~5000	<1000

	动物	植物
特有结构	?	细胞壁(初生壁和次生壁)、液泡和叶绿体
包埋方法	冷冻包埋和石蜡包埋	冷冻包埋
组织切片	相对简单	相对困难, 高度木质化组织容易开裂、液泡易产生结晶等
染色方法	苏木精-伊红染色和ssDNA染色	甲苯铵蓝染色、ssDNA染色和钙白染色
组织透化	透化细胞膜	透化细胞壁和细胞膜, 且不同植物细胞的细胞壁成分存在较大异质性
组织移除	相对简单	高度成熟组织的降解可能需要较长的时间和苛刻的组织移除操作, 可能会影响逆转录产物
参考基因组	参考基因组较为完善	参考基因组有待进一步完善
技术平台	大量时空组技术优先适配于动物组织	时空组技术在植物组织中的应用条件仍有待进一步优化
时空组学文献数量	~5000	<1000

转录组技术				空间分辨率	细胞通量	优缺点	应用范围		参考文献
传统转录组学				组织水平	高	+ 成本低, 检测速度快 ? 掩盖了细胞的时空异质性	动植物微生物		Costa et al., 2010
单细胞转录组学				单细胞水平	高	+ 通量高, 检测深度较深 ? 忽略了细胞的空间信息	动植物微生物		Kolodziejczyk et al., 2015
时空转录组学		基于微解剖基因表达的技术	LCM	单细胞水平	低	+ 可人工挑选感兴趣的细胞 ? 通量低, 操作难度大	动植物微生物		Emmert-buck et al., 1996
			TIVA	单细胞水平	低	+ 能应用于活细胞 ? 通量低, 分析结果有限	动物		Lovatt et al., 2014
			Tomo-seq	单个切片	低	+ 可构建3D轮廓表达谱 ? 需多个相同的生物样本, 不能应用于人体样本	动物		Junker et al., 2014
			Geo-seq	单细胞水平	低	+ 比LCM更灵敏 ? 通量低	动物		Chen et al., 2017
			NICHE-seq	单细胞水平	高	+ 通量高 ? 只能确定特定生态位的空间位置, 不能应用于人体样本	动物		Medaglia et al., 2017
			proximID	单细胞水平	低	+ 保留部分细胞相互作用的互作结构 ? 需基于LCM进行细胞分离, 通量低	动物		Boisset et al., 2018
		原位杂交技术	smFISH	亚细胞水平	低	+ 灵敏度高, 检测效率相对较高 ? 检测的RNA数量有限	动植物微生物		Femino et al., 1998
			RNA-scope	亚细胞水平	低	+ 特异性高, 信噪比极高, 灵敏度高 ? 通量低	动植物微生物		Wang et al., 2013
			seqFISH	亚细胞水平	低	+ 高度多重化 ? 需要专门的设备, 视野受限	动物		Lubeck et al., 2014
			MERFISH	单细胞水平	较高	+ 高度多重化 ? 需要专门的设备, 视野受限	动物		Chen et al., 2015
			osmFISH	亚细胞水平	较高	+ 可检测更大的组织区域, 半自动化 ? 通量相对较低	动物		Codeluppi et al., 2018
			seqFISH+	单细胞水平	较高	+ 极度多重化 ? 需要专门的设备, 视野受限	动物		Eng et al., 2019
			DNA microscpy	单细胞水平	较高	+ 不依赖光或任何类型的光学器件进行组织的基因表达成像 ? 仅在乳腺癌细胞中应用过	动物		Weinstein et al., 2019
		原位测序技术	ISS using padlock probes	亚细胞水平	较低	+ 亚细胞分辨率检测SNV的能力 ? 转录本检测灵敏度低	动植物微生物		Ke et al., 2013
			FISSEQ	亚细胞水平	较低	+ 可捕获所有类型的RNA ? 转录本检测灵敏度相对较低	动物		Lee et al., 2014
			Barista Seq	亚细胞水平	较低	+ 探针缺口内读取长度可达15个碱基 ? 仅在培养细胞上应用过	动物		Chen et al., 2018
			STARmap	亚细胞水平	较高	+ 不需要反转录步骤, 灵敏度高 ? 转录本检测灵敏度低, 视野有限	动物		Mano et al., 2019
			INSTA-seq	亚细胞水平	较高	+ 一种非靶标的方法, 原位测序区域条形码, 异位测序转录本 ? 检测灵敏度相对较低	动物		Fürth et al., 2019
	原位捕获技术		ST/10× Visium	100 μm/ 55 μm	高	+ 可检测完整组织切片中总mRNA ? 条形码区域可能覆盖多个细胞, 未达到单细胞水平	动植物微生物		St?hl et al., 2016
			Nanostring GeoMx	10 μm	高	+ 在蛋白质/RNA分析之间选择高度自动化 ? 使用较小ROI时灵敏度低, 需要手动选择区域	动物微生物		Merritt et al., 2020
			Slide-seq	10 μm	高	+ 高分辨率 ? 检测灵敏度相对较低	动物		Rodriques et al., 2019
时空转录组学	原位捕获技术		APEX-seq	亚细胞水平	高	+ 可以在活细胞中进行 ? 需要让特定APEX2酶在特定的亚细胞区域重组表达, 并不适用于正常组织		动物		Fazal et al., 2019
			HDST	2 μm	高	+ 高分辨率 ? 稀疏数据需要分箱, 检测灵敏度相对较低		动物		Vickovic et al., 2019
			DBiT-seq	10 μm	高	+ 可同时构建mRNA和蛋白质的空间多组学图谱 ? 检测灵敏度相对较低		动物		Liu et al., 2020
			Stereo-seq	0.5 μm	高	+ 亚细胞分辨率和厘米级视野 ? 检测灵敏度相对较低		动植物微生物		Chen et al., 2022
			Seq-scope	0.5 μm	高	+ 亚细胞分辨率 ? 检测灵敏度相对较低		动物		Cho et al., 2021
			PIXEL-seq	1 μm	高	+ 亚细胞分辨率, 成本低 ? 检测灵敏度相对较低		动物		Fu et al., 2021, 2022
			sci-Space	单细胞水平	高	+ 利用sci-RNA-seq进行测序, 检测灵敏度相对较高 ? 依赖于sci-Plex进行空间信息记录, 分辨率相对较低, 只进行核基因测序		动物		Srivatsan et al., 2020, 2021

转录组技术				空间分辨率	细胞通量	优缺点	应用范围		参考文献
传统转录组学				组织水平	高	+ 成本低, 检测速度快 ? 掩盖了细胞的时空异质性	动植物微生物		Costa et al., 2010
单细胞转录组学				单细胞水平	高	+ 通量高, 检测深度较深 ? 忽略了细胞的空间信息	动植物微生物		Kolodziejczyk et al., 2015
时空转录组学		基于微解剖基因表达的技术	LCM	单细胞水平	低	+ 可人工挑选感兴趣的细胞 ? 通量低, 操作难度大	动植物微生物		Emmert-buck et al., 1996
			TIVA	单细胞水平	低	+ 能应用于活细胞 ? 通量低, 分析结果有限	动物		Lovatt et al., 2014
			Tomo-seq	单个切片	低	+ 可构建3D轮廓表达谱 ? 需多个相同的生物样本, 不能应用于人体样本	动物		Junker et al., 2014
			Geo-seq	单细胞水平	低	+ 比LCM更灵敏 ? 通量低	动物		Chen et al., 2017
			NICHE-seq	单细胞水平	高	+ 通量高 ? 只能确定特定生态位的空间位置, 不能应用于人体样本	动物		Medaglia et al., 2017
			proximID	单细胞水平	低	+ 保留部分细胞相互作用的互作结构 ? 需基于LCM进行细胞分离, 通量低	动物		Boisset et al., 2018
		原位杂交技术	smFISH	亚细胞水平	低	+ 灵敏度高, 检测效率相对较高 ? 检测的RNA数量有限	动植物微生物		Femino et al., 1998
			RNA-scope	亚细胞水平	低	+ 特异性高, 信噪比极高, 灵敏度高 ? 通量低	动植物微生物		Wang et al., 2013
			seqFISH	亚细胞水平	低	+ 高度多重化 ? 需要专门的设备, 视野受限	动物		Lubeck et al., 2014
			MERFISH	单细胞水平	较高	+ 高度多重化 ? 需要专门的设备, 视野受限	动物		Chen et al., 2015
			osmFISH	亚细胞水平	较高	+ 可检测更大的组织区域, 半自动化 ? 通量相对较低	动物		Codeluppi et al., 2018
			seqFISH+	单细胞水平	较高	+ 极度多重化 ? 需要专门的设备, 视野受限	动物		Eng et al., 2019
			DNA microscpy	单细胞水平	较高	+ 不依赖光或任何类型的光学器件进行组织的基因表达成像 ? 仅在乳腺癌细胞中应用过	动物		Weinstein et al., 2019
		原位测序技术	ISS using padlock probes	亚细胞水平	较低	+ 亚细胞分辨率检测SNV的能力 ? 转录本检测灵敏度低	动植物微生物		Ke et al., 2013
			FISSEQ	亚细胞水平	较低	+ 可捕获所有类型的RNA ? 转录本检测灵敏度相对较低	动物		Lee et al., 2014
			Barista Seq	亚细胞水平	较低	+ 探针缺口内读取长度可达15个碱基 ? 仅在培养细胞上应用过	动物		Chen et al., 2018
			STARmap	亚细胞水平	较高	+ 不需要反转录步骤, 灵敏度高 ? 转录本检测灵敏度低, 视野有限	动物		Mano et al., 2019
			INSTA-seq	亚细胞水平	较高	+ 一种非靶标的方法, 原位测序区域条形码, 异位测序转录本 ? 检测灵敏度相对较低	动物		Fürth et al., 2019
	原位捕获技术		ST/10× Visium	100 μm/ 55 μm	高	+ 可检测完整组织切片中总mRNA ? 条形码区域可能覆盖多个细胞, 未达到单细胞水平	动植物微生物		St?hl et al., 2016
			Nanostring GeoMx	10 μm	高	+ 在蛋白质/RNA分析之间选择高度自动化 ? 使用较小ROI时灵敏度低, 需要手动选择区域	动物微生物		Merritt et al., 2020
			Slide-seq	10 μm	高	+ 高分辨率 ? 检测灵敏度相对较低	动物		Rodriques et al., 2019
时空转录组学	原位捕获技术		APEX-seq	亚细胞水平	高	+ 可以在活细胞中进行 ? 需要让特定APEX2酶在特定的亚细胞区域重组表达, 并不适用于正常组织		动物		Fazal et al., 2019
			HDST	2 μm	高	+ 高分辨率 ? 稀疏数据需要分箱, 检测灵敏度相对较低		动物		Vickovic et al., 2019
			DBiT-seq	10 μm	高	+ 可同时构建mRNA和蛋白质的空间多组学图谱 ? 检测灵敏度相对较低		动物		Liu et al., 2020
			Stereo-seq	0.5 μm	高	+ 亚细胞分辨率和厘米级视野 ? 检测灵敏度相对较低		动植物微生物		Chen et al., 2022
			Seq-scope	0.5 μm	高	+ 亚细胞分辨率 ? 检测灵敏度相对较低		动物		Cho et al., 2021
			PIXEL-seq	1 μm	高	+ 亚细胞分辨率, 成本低 ? 检测灵敏度相对较低		动物		Fu et al., 2021, 2022
			sci-Space	单细胞水平	高	+ 利用sci-RNA-seq进行测序, 检测灵敏度相对较高 ? 依赖于sci-Plex进行空间信息记录, 分辨率相对较低, 只进行核基因测序		动物		Srivatsan et al., 2020, 2021