生物技术通报 ›› 2021, Vol. 37 ›› Issue (1): 145-154.doi: 10.13560/j.cnki.biotech.bull.1985.2020-0396
收稿日期:
2020-04-09
出版日期:
2021-01-26
发布日期:
2021-01-15
作者简介:
朱庆元,男,硕士,研究方向:动物学;E-mail: ZHU Qing-yuan(), LI Tian-qing()
Received:
2020-04-09
Published:
2021-01-26
Online:
2021-01-15
摘要:
单细胞转录组测序(Single-cell RNA sequencing,scRNA-seq)可以在单细胞水平描绘出每个细胞同一基因的表达量在不同细胞间的表达水平差异,使得在单细胞水平重新认识各种组织器官成为可能。目前对心脏的测序研究正从传统的普通转录组水平过渡到单细胞水平,对小鼠和人的心脏的测序陆续地发表出来。概述了scRNA-seq在心脏发育、疾病以及医学中的应用,讨论了scRNA-seq 技术在胚胎心脏发育、心脏细胞的异质性以及在心脏血管方面、多能干细胞分化心血管细胞模型和先天性心脏畸形的进展和存在问题,对scRNA-seq技术对心脏发育、心脏再生、心脏病和单细胞个性化医疗等方面作出展望。
朱庆元, 李天晴. 单细胞转录组测序技术在心脏发育、疾病以及医学中的应用[J]. 生物技术通报, 2021, 37(1): 145-154.
ZHU Qing-yuan, LI Tian-qing. Applications of Single-cell RNA Sequencing in Heart Development,Disease and Medicine[J]. Biotechnology Bulletin, 2021, 37(1): 145-154.
发表年份 | 测序技术 | UMI长度/bp | 基因数 | 精度 | 单细胞捕获方法 | 扩增噪音 | 单个细胞成本 | 参考文献 |
---|---|---|---|---|---|---|---|---|
2012 | Smart-seq/C1 | 0 | 中 | 中 | 平板 | 高 | 高 | [9] |
2014 | Smart-seq2 | 0 | 高 | 高 | 平板 | 中高 | 高 | [11] |
2014 | MARS-seq | 8 | 低 | 低 | 微流 | 中 | 高 | [12] |
2015 | Drop-seq | 8 | 低 | 中高 | 液滴 | 低 | 中 | [14] |
2016 | CEL-seq2/C1 | 6 | 中 | 低 | 微流 | 低 | 高 | [20] |
2016 | SORT-seq | 4 | 高 | 高 | 平板 | 低 | 中 | [21] |
2017 | 10×Genomics | 10 | 高 | 中 | 油滴 | 低 | 低 | [15] |
2018 | mcSCRB-seq | 10 | 中 | 中 | 平板 | 低 | 高 | [22] |
表1 主要scRNA-seq测序技术
发表年份 | 测序技术 | UMI长度/bp | 基因数 | 精度 | 单细胞捕获方法 | 扩增噪音 | 单个细胞成本 | 参考文献 |
---|---|---|---|---|---|---|---|---|
2012 | Smart-seq/C1 | 0 | 中 | 中 | 平板 | 高 | 高 | [9] |
2014 | Smart-seq2 | 0 | 高 | 高 | 平板 | 中高 | 高 | [11] |
2014 | MARS-seq | 8 | 低 | 低 | 微流 | 中 | 高 | [12] |
2015 | Drop-seq | 8 | 低 | 中高 | 液滴 | 低 | 中 | [14] |
2016 | CEL-seq2/C1 | 6 | 中 | 低 | 微流 | 低 | 高 | [20] |
2016 | SORT-seq | 4 | 高 | 高 | 平板 | 低 | 中 | [21] |
2017 | 10×Genomics | 10 | 高 | 中 | 油滴 | 低 | 低 | [15] |
2018 | mcSCRB-seq | 10 | 中 | 中 | 平板 | 低 | 高 | [22] |
细胞类型 | 共有标记基因 | 亚型 | 标记基因 | 结合空间转录组定位 |
---|---|---|---|---|
心肌 | TNNT2、TNNC1、ACTC1、TNNI3、ACTN2、NKX2-5、ENO3、COX6A2 | 心室肌 | MYH7、MYL2、LBH、NAV1、HAND1 | 心室 |
心房肌 | MYH6、TBX5、PAM、HNF4A | 心房 | ||
小梁肌 | ANGPT1、COL2A1、ITGA6、RELN、SLIT2、CRABP2 | |||
myoz2心肌 | MYOZ2、FABP3 | 心房和心室 | ||
表达细胞外基质基因心肌 | OPHN1、FOXK1、COL2A1、DCN | |||
致密化心肌 | ||||
内皮 | RAMP2、EMCN、PECAM1、CDH5、TIE1、TEK、HES1 | 冠状动脉内皮 | FABP4、CD36 | 致密化心肌 |
血管内皮 | ELN、FNLN5 | |||
瓣膜内皮 | NTRK2、NFATC1 | |||
心内膜内皮 | CDH11、NPR3 | 小梁肌 | ||
心外膜 | UPK3B、ALDH1A2、WT1、TBX18 | 心外膜 | CFB、C3、PRG4、ITLN1 | 心脏最外层包绕心脏 |
心外膜前体细胞 | KLK6、CRABP2、TCF21 | 房室区心外膜下间质 | ||
成纤维细胞 | DCN、COL1A1、FBLN1、LUM、TCF21 | 骨骼肌结缔组织样成纤维 | 流出道、瓣膜 | |
小血管发育成纤维 | 心外膜下 | |||
大血管发育成纤维 | 靠近流出道 | |||
平滑肌样成纤维 | 流出道、房室区心外膜下间质 | |||
神经嵴细胞 | ISL1、STMN2 | 纵隔间质和流出道 | ||
施旺细胞 | ALDH1A1、DHH | 纵隔间质和流出道房室外膜下间质 | ||
瓣膜细胞 | APCDD1、EDIL3、SCRG1、SLN、NR4A2 |
表2 心脏细胞主要类型及其基因表达特点和空间定位
细胞类型 | 共有标记基因 | 亚型 | 标记基因 | 结合空间转录组定位 |
---|---|---|---|---|
心肌 | TNNT2、TNNC1、ACTC1、TNNI3、ACTN2、NKX2-5、ENO3、COX6A2 | 心室肌 | MYH7、MYL2、LBH、NAV1、HAND1 | 心室 |
心房肌 | MYH6、TBX5、PAM、HNF4A | 心房 | ||
小梁肌 | ANGPT1、COL2A1、ITGA6、RELN、SLIT2、CRABP2 | |||
myoz2心肌 | MYOZ2、FABP3 | 心房和心室 | ||
表达细胞外基质基因心肌 | OPHN1、FOXK1、COL2A1、DCN | |||
致密化心肌 | ||||
内皮 | RAMP2、EMCN、PECAM1、CDH5、TIE1、TEK、HES1 | 冠状动脉内皮 | FABP4、CD36 | 致密化心肌 |
血管内皮 | ELN、FNLN5 | |||
瓣膜内皮 | NTRK2、NFATC1 | |||
心内膜内皮 | CDH11、NPR3 | 小梁肌 | ||
心外膜 | UPK3B、ALDH1A2、WT1、TBX18 | 心外膜 | CFB、C3、PRG4、ITLN1 | 心脏最外层包绕心脏 |
心外膜前体细胞 | KLK6、CRABP2、TCF21 | 房室区心外膜下间质 | ||
成纤维细胞 | DCN、COL1A1、FBLN1、LUM、TCF21 | 骨骼肌结缔组织样成纤维 | 流出道、瓣膜 | |
小血管发育成纤维 | 心外膜下 | |||
大血管发育成纤维 | 靠近流出道 | |||
平滑肌样成纤维 | 流出道、房室区心外膜下间质 | |||
神经嵴细胞 | ISL1、STMN2 | 纵隔间质和流出道 | ||
施旺细胞 | ALDH1A1、DHH | 纵隔间质和流出道房室外膜下间质 | ||
瓣膜细胞 | APCDD1、EDIL3、SCRG1、SLN、NR4A2 |
[1] | Sylva M, van den Hoff MJ, Moorman AF. Development of the human heart[J]. American Journal of Medical Genetics Part A, 2014,164(6):1347-1371. |
[2] | Meilhac SM, Buckingham ME. The deployment of cell lineages that form the mammalian heart[J]. Nature Reviews Cardiology, 2018,15(11):705-724. |
[3] |
Buckingham M, Meilhac S, Zaffran S. Building the mammalian heart from two sources of myocardial cells[J]. Nature Reviews Genetics, 2005,6(11):826-835.
URL pmid: 16304598 |
[4] | McFadden DG, Barbosa AC, Richardson JA, et al. The Hand1 and Hand2 transcription factors regulate expansion of the embryonic cardiac ventricles in a gene dosage-dependent manner[J]. Development, 2005,132(1):189-201. |
[5] | Cui Y, Zheng Y, Liu X, et al. Single-cell transcriptome analysis maps the developmental track of the human heart[J]. Cell Reports, 2019, 26(7):1934-1950. e1935. |
[6] | Sahara M, Santoro F, Sohlmér J, et al. Population and single-cell analysis of human cardiogenesis reveals unique LGR5 ventricular progenitors in embryonic outflow tract[J]. Developmental Cell, 2019, 48(4):475-490. e477. |
[7] | Tang F, Barbacioru C, Wang Y, et al. mRNA-Seq whole-transcriptome analysis of a single cell[J]. Nature Methods, 2009,6(5):377. |
[8] |
Islam S, Kjällquist U, Moliner A, et al. Characterization of the single-cell transcriptional landscape by highly multiplex RNA-seq[J]. Genome Research, 2011,21(7):1160-1167.
URL pmid: 21543516 |
[9] | Ramsköld D, Luo S, Wang YC, et al. Full-length mRNA-seq from single-cell levels of RNA and individual circulating tumor cells[J]. Nature Biotechnology, 2012,30(8):777. |
[10] |
Hashimshony T, Wagner F, Sher N, et al. CEL-Seq:single-cell RNA-seq by multiplexed linear amplification[J]. Cell Reports, 2012,2(3):666-673.
URL pmid: 22939981 |
[11] |
Picelli S, Björklund ÅK, Faridani OR, et al. Smart-seq2 for sensitive full-length transcriptome profiling in single cells[J]. Nature Methods, 2013,10(11):1096-1098.
URL pmid: 24056875 |
[12] |
Jaitin DA, Kenigsberg E, Keren-Shaul H, et al. Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types[J]. Science, 2014,343(6172):776-779.
URL pmid: 24531970 |
[13] |
Macosko EZ, Basu A, Satija R, et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets[J]. Cell, 2015,161(5):1202-1214.
URL pmid: 26000488 |
[14] |
Klein AM, Mazutis L, Akartuna I, et al. Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells[J]. Cell, 2015,161(5):1187-1201.
URL pmid: 26000487 |
[15] |
Zheng GXY, Terry JM, Belgrader P, et al. Massively parallel digital transcriptional profiling of single cells[J]. Nature Communications, 2017,8:14049.
doi: 10.1038/ncomms14049 URL pmid: 28091601 |
[16] | Gierahn TM, Wadsworth MH, Hughes TK, et al. Seq-Well:portable, low-cost RNA sequencing of single cells at high throughput[J]. Nature Methods, 2017,14(4):395-398. |
[17] | Han X, Wang R, Zhou Y, et al. Mapping the mouse cell atlas by microwell-seq[J]. Cell, 2018,173(5):1307. |
[18] | Rosenberg AB, Roco CM, Muscat RA, et al. Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding[J]. Science, 2018,360(6385):176-182. |
[19] | Rodriques SG, Stickels RR, Goeva A, et al. Slide-seq:A scalable technology for measuring genome-wide expression at high spatial resolution[J]. Science, 2019,363(6434):1463-1467. |
[20] | Hashimshony T, Senderovich N, Avital G, et al. CEL-Seq2:sensitive highly-multiplexed single-cell RNA-Seq[J]. Genome Biology, 2016,17:77. |
[21] |
Muraro MJ, Dharmadhikari G, Grün D, et al. A single-cell transcriptome atlas of the human pancreas[J]. Cell Systems, 2016,3(4):385-394.
URL pmid: 27693023 |
[22] |
Bagnoli JW, Ziegenhain C, Janjic A, et al. Sensitive and powerful single-cell RNA sequencing using mcSCRB-seq[J]. Nature Communications, 2018,9(1):2937.
doi: 10.1038/s41467-018-05347-6 URL pmid: 30050112 |
[23] |
Li G, Xu A, Sim S, et al. Transcriptomic profiling maps anatomically patterned subpopulations among single embryonic cardiac cells[J]. Developmental Cell, 2016,39(4):491-507. e3.
URL pmid: 27840109 |
[24] | DeLaughter DM, Bick AG, Wakimoto H, et al. Single-cell resolution of temporal gene expression during heart development[J]. Developmental Cell, 2016,39(4):480-490. |
[25] | Lescroart F, Wang X, Lin X, et al. Defining the earliest step of cardiovascular lineage segregation by single-cell RNA-seq[J]. Science, 2018,359(6380):1177-1181. |
[26] |
Asp M, Giacomello S, Larsson L, et al. A spatiotemporal organ-wide gene expression and cell atlas of the developing human heart[J]. Cell, 2019,179(7):1647-1660. e1619.
doi: 10.1016/j.cell.2019.11.025 URL pmid: 31835037 |
[27] | Su T, Stanley G, Sinha R, et al. Single-cell analysis of early progenitor cells that build coronary arteries[J]. Nature, 2018,559(7714):356-362. |
[28] |
Kalluri AS, Vellarikkal SK, Edelman ER, et al. Single-cell analysis of the normal mouse aorta reveals functionally distinct endothelial cell populations[J]. Circulation, 2019,140(2):147-163.
doi: 10.1161/CIRCULATIONAHA.118.038362 URL pmid: 31146585 |
[29] |
McDonald AI, Shirali AS, Aragón R, et al. Endothelial regeneration of large vessels is a biphasic process driven by local cells with distinct proliferative capacities[J]. Cell Stem Cell, 2018,23(2):210-225.
doi: 10.1016/j.stem.2018.07.011 URL |
[30] | Wirka RC, Wagh D, Paik DT, et al. Atheroprotective roles of smooth muscle cell phenotypic modulation and the TCF21 disease gene as revealed by single-cell analysis[J]. Nature Medicine, 2019,25(8):1280-1289. |
[31] | Yao F, Yu P, Li Y, et al. Histone variant H2A. Z is required for the maintenance of smooth muscle cell identity as revealed by single-cell transcriptomics[J]. Circulation, 2018,138(20):2274-2288. |
[32] |
Cochain C, Vafadarnejad E, Arampatzi P, et al. Single-cell RNA-seq reveals the transcriptional landscape and heterogeneity of aortic macrophages in murine atherosclerosis[J]. Circulation Research, 2018,122(12):1661-1674.
doi: 10.1161/CIRCRESAHA.117.312509 URL pmid: 29545365 |
[33] | Winkels H, Ehinger E, Vassallo M, et al. Atlas of the immune cell repertoire in mouse atherosclerosis defined by single-cell RNA-sequencing and mass cytometry[J]. Circulation Research, 2018,122(12):1675-1688. |
[34] |
Friedman CE, Nguyen Q, Lukowski SW, et al. Single-cell transcriptomic analysis of cardiac differentiation from human PSCs reveals HOPX-dependent cardiomyocyte maturation[J]. Cell Stem Cell, 2018,23(4):586-598.
doi: 10.1016/j.stem.2018.09.009 URL pmid: 30290179 |
[35] | Churko JM, Garg P, Treutlein B, et al. Defining human cardiac transcription factor hierarchies using integrated single-cell heterogeneity analysis[J]. Nature Communications, 2018,9(1):4906. |
[36] |
Paik DT, Tian L, Lee J, et al. Large-scale single-cell RNA-seq reveals molecular signatures of Heterogeneous populations of human induced pluripotent stem cell-derived endothelial cells[J]. Circulation Research, 2018,123(4):443-450.
doi: 10.1161/CIRCRESAHA.118.312913 URL pmid: 29986945 |
[37] | McCracken IR, Taylor RS, Kok FO, et al. Transcriptional dynamics of pluripotent stem cell-derived endothelial cell differentiation revealed by single-cell RNA sequencing[J]. European Heart Journal, 2020,41(9):1024-1036. |
[38] | Gladka MM, Molenaar B, de Ruiter H, et al. ingle-cell sequencing of the healthy and diseased heart reveals cytoskeleton-associated protein 4 as a new modulator of fibroblasts activation[J]. Circulation, 2018,138(2):166-180. |
[39] | Honkoop H, de Bakker DE, Aharonov A, et al. Single-cell analysis uncovers that metabolic reprogramming by ErbB2 signaling is essential for cardiomyocyte proliferation in the regenerating heart[J]. eLife, 2019,8:e50163. |
[40] | Paik DT, Rai M, Ryzhov S, et al. Wnt10b gain-of-function improves cardiac repair by arteriole formation and attenuation of fibrosis[J]. Circulation Research, 2015,117(9):804-816. |
[41] | Wu Q, Liu Q, Zhan J, et al. Cited2 regulates proliferation and survival in young and old mouse cardiac stem cells[J]. BMC Molecular and Cell Biology, 2019,20(1):25. |
[42] | Elliott DA, Kirk EP, Yeoh T, et al. Cardiac homeobox gene NKX2-5 mutations and congenital heart disease:Associations with atrial septal defect and hypoplastic left heart syndrome[J]. Journal of the American College of Cardiology, 2003,41(11):2072-2076. |
[43] | Dong X, Fan P, Tian T, et al. Recent advancements in the molecular genetics of left ventricular noncompaction cardiomyopathy[J]. Clinica Chimica Acta, 2017,465:40-44. |
[44] | Grego-Bessa J, Luna-Zurita L, del Monte G, et al. Notch signaling is essential for ventricular chamber development[J]. Developmental Cell, 2007,12(3):415-429. |
[45] | Finsterer J, Stoellberger C, Towbin JA. Left ventricular noncompaction cardiomyopathy:cardiac, neuromuscular, and genetic factors[J]. Nature Reviews Cardiology, 2017,14(4):224. |
[46] | Lin X, Huo Z, Liu X, et al. A novel GATA6 mutation in patients with tetralogy of Fallot or atrial septal defect[J]. Journal of Human Genetics, 2010,55(10):662-667. |
[47] | Maitra M, Koenig SN, Srivastava D, et al. Identification of GATA6 sequence variants in patients with congenital heart defects[J]. Pediatric Research, 2010,68(4):281. |
[48] | Holm H, Gudbjartsson DF, Sulem P, et al. A rare variant in MYH6 is associated with high risk of sick sinus syndrome[J]. Nature Genetics, 2011,43(4):316. |
[49] | Gollob MH, Jones DL, Krahn AD, et al. Somatic mutations in the connexin 40 gene(GJA5)in atrial fibrillation[J]. New England Journal of Medicine, 2006,354(25):2677-2688. |
[50] | Nomura S, Satoh M, Fujita T, et al. Cardiomyocyte gene programs encoding morphological and functional signatures in cardiac hypertrophy and failure[J]. Nature Communications, 2018,9(1):4435. |
[51] | Chen J, He J, Ni R, et al. Cerebrovascular injuries induce lymphatic invasion into brain parenchyma to guide vascular regeneration in zebrafish[J]. Developmental Cell, 2019,49(5):697-710. e695. |
[52] | Porrello ER, Mahmoud AI, Simpson E, et al. Transient regenerative potential of the neonatal mouse heart[J]. Science, 2011,331(6020):1078-1080. |
[53] | Cai CL, Martin JC, Sun Y, et al. A myocardial lineage derives from Tbx18 epicardial cells[J]. Nature, 2008,454(7200):104-108. |
[54] | Coffee M, Biswanath S, Bolesani E, et al. Heart muscle tissue engineering[M]// In:Essential Current Concepts in Stem Cell Biology. Springer, 2020: 99-121. |
[1] | 吴昊, 刘紫微, 郑颖, 戴雅文, 时权. 单细胞水平解析人牙龈间充质干细胞异质性[J]. 生物技术通报, 2023, 39(7): 325-332. |
[2] | 赵艳坤, 刘慧敏, 孟璐, 王成, 王加启, 郑楠. 大肠埃希菌异质性耐药的研究进展[J]. 生物技术通报, 2022, 38(9): 59-71. |
[3] | 寇佳怡, 王玉玲, 曾睿琳, 兰道亮. 单细胞转录组测序技术及在哺乳动物上的应用[J]. 生物技术通报, 2022, 38(11): 41-48. |
[4] | 张淼, 孙祥瑞, 徐春明. 单细胞RNA测序数据分析方法研究进展[J]. 生物技术通报, 2021, 37(1): 52-59. |
[5] | 过冬冬, 孙芬, 贺轩昂, 羊东晔, 黄来强. 单细胞测序技术在肝脏疾病的应用与展望[J]. 生物技术通报, 2021, 37(1): 137-144. |
[6] | 曹燕亭, 刘延峰, 李江华, 刘龙, 堵国成. 基于细胞亚群调控提升生物合成效率的研究进展[J]. 生物技术通报, 2020, 36(4): 19-25. |
[7] | 邢亚欣, 黄火清, 苏小运. 一个来源于稻平脐蠕孢的α-阿拉伯呋喃糖苷酶[J]. 生物技术通报, 2020, 36(4): 84-92. |
[8] | 王丹蕊, 沈文丽, 魏子艳, 王尚, 邓晔. 单细胞测序技术在微生物生态领域中的应用[J]. 生物技术通报, 2020, 36(10): 237-246. |
[9] | 肖尚,邓崇飞,柯军,鄢成伟,孙文正,杨彬. pH对重组CHO细胞生长、单抗表达及质量的影响[J]. 生物技术通报, 2015, 31(12): 256-261. |
[10] | 周志军, 尚娜, 常岩林, 石福明. DNA条形码揭示日本纺织娘(Mecopoda niponensis)个体内和个体间的序列变异[J]. 生物技术通报, 2014, 0(5): 129-136. |
[11] | 付元帅;施志仪;. MicroRNA与动物发育[J]. , 2010, 0(01): 30-36. |
[12] | 杨淑培. 同济医学院发现可能导致中国人猝死的基因突变点[J]. , 2001, 0(02): 49-49. |
阅读次数 | ||||||
全文 |
|
|||||
摘要 |
|
|||||