畜牧兽医学报 ›› 2024, Vol. 55 ›› Issue (8): 3276-3287.doi: 10.11843/j.issn.0366-6964.2024.08.002
张肖旭(), 李昊, 冯平捷, 杨豪, 李新月, 吕冉, 潘章源*(
), 储明星*(
)
收稿日期:
2024-02-02
出版日期:
2024-08-23
发布日期:
2024-08-28
通讯作者:
潘章源,储明星
E-mail:zhangxiaoxu_dk@163.com;zhypan01@163.com;mxchu@263.net
作者简介:
张肖旭(2000-),女,山东邹城人,博士生,主要从事动物遗传育种研究,E-mail: zhangxiaoxu_dk@163.com
基金资助:
Xiaoxu ZHANG(), Hao LI, Pingjie FENG, Hao YANG, Xinyue LI, Ran LÜ, Zhangyuan PAN*(
), Mingxing CHU*(
)
Received:
2024-02-02
Online:
2024-08-23
Published:
2024-08-28
Contact:
Zhangyuan PAN, Mingxing CHU
E-mail:zhangxiaoxu_dk@163.com;zhypan01@163.com;mxchu@263.net
摘要:
单细胞转录组测序技术(single cell RNA sequencing, scRNA-seq)能够以高精度分辨率鉴定单个细胞类型和细胞状态,打破普通转录组测序(bulk RNA sequencing, RNA-seq)无法探究目标细胞具体表达特征的困境,在各个领域的探索中起到重要作用,目前广泛应用于人类及小鼠发育生物学、肿瘤学、免疫学、复杂疾病、肠道微生物组及临床应用等诸多领域。近年来,scRNA-seq在畜牧业领域也开展了一些开创性的研究并获得了一系列的成果,主要集中在动物繁殖性能、胚胎发育、关键性状解析等方面,但相较于在人类上的应用还较为薄弱,在其他领域的应用也仍有待深入。本文主要综述了scRNA-seq的工作流程及其在家养动物中应用的研究进展,以期为提高scRNA-seq分析效率以及在家养动物中的创新应用提供参考。
中图分类号:
张肖旭, 李昊, 冯平捷, 杨豪, 李新月, 吕冉, 潘章源, 储明星. 单细胞转录组测序技术在家养动物中的应用[J]. 畜牧兽医学报, 2024, 55(8): 3276-3287.
Xiaoxu ZHANG, Hao LI, Pingjie FENG, Hao YANG, Xinyue LI, Ran LÜ, Zhangyuan PAN, Mingxing CHU. Application of Single-Cell Transcriptome Sequencing Technology in Domesticated Animals[J]. Acta Veterinaria et Zootechnica Sinica, 2024, 55(8): 3276-3287.
表 1
scRNA-seq与其他技术的结合及新的软件工具"
技术/工具 Technology/tools | 应用 Application | 参考文献 References |
scRNA-seq+细胞示踪技术 scRNA-seq+cellular tracer technology | 肝细胞移植后状态的变化和分区特征研究 | [ |
RIBOmap | 小鼠脑组织中细胞类型特异性和脑区特异性翻译调控研究 | [ |
scRNA-seq+成像质谱分析scRNA-seq+IMS | 活化的恒定自然杀伤T细胞在胰腺癌肝转移中的保护功能研究 | [ |
autoCell | 高维稀疏scRNA-seq数据集的分布推断 | [ |
scGCL | scRNA-seq数据估算 | [ |
MCGL | scRNA-seq数据集的细胞聚类性能提高 | [ |
CAME | 跨物种细胞类型分配和基因模块提取 | [ |
scRNA-tools | 分析和处理scRNA-seq数据 | [ |
1 | 熊和丽, 沙茜, 刘韶娜, 等. 单细胞转录组测序技术在动物上的应用研究[J]. 生物技术通报, 2022, 38 (3): 226- 233. |
XIONG H L , SHA Q , LIU S N , et al. Application of single-cell transcriptome sequencing in animals[J]. Biotechnology Bulletin, 2022, 38 (3): 226- 233. | |
2 |
CHOE K , PAK U , PANG Y , et al. Advances and challenges in spatial transcriptomics for developmental biology[J]. Biomolecules, 2023, 13 (1): 156.
doi: 10.3390/biom13010156 |
3 | 李丽娟, 师书玥, 张村宇, 等. 单细胞转录组测序技术原理及其应用[J]. 中国畜牧杂志, 2019, 55 (2): 15- 21. |
LI L J , SHI S Y , ZHANG C Y , et al. Principle and application of single cell transceriptome sequencing[J]. Chinese Journal of Animal Science, 2019, 55 (2): 15- 21. | |
4 |
XU J L , XU J L , MENG Y J , et al. Graph embedding and Gaussian mixture variational autoencoder network for end-to-end analysis of single-cell RNA sequencing data[J]. Cell Rep Methods, 2023, 3 (1): 100382.
doi: 10.1016/j.crmeth.2022.100382 |
5 |
XU K , CHEONG C , VELDSMAN W P , et al. Accurate and interpretable gene expression imputation on scRNA-seq data using IGSimpute[J]. Brief Bioinform, 2023, 24 (3): bbad124.
doi: 10.1093/bib/bbad124 |
6 |
TAN Z Y , CHEN X R , ZUO J M , et al. Comprehensive analysis of scRNA-Seq and bulk RNA-Seq reveals dynamic changes in the tumor immune microenvironment of bladder cancer and establishes a prognostic model[J]. J Transl Med, 2023, 21 (1): 223.
doi: 10.1186/s12967-023-04056-z |
7 |
LIU X Y , SHEN Q L , ZHANG S H . Cross-species cell-type assignment from single-cell RNA-seq data by a heterogeneous graph neural network[J]. Genome Res, 2023, 33 (1): 96- 111.
doi: 10.1101/gr.276868.122 |
8 |
LU S , KELEŞ S . Debiased personalized gene coexpression networks for population-scale scRNA-seq data[J]. Genome Res, 2023, 33 (6): 932- 947.
doi: 10.1101/gr.277363.122 |
9 |
NAYDENOV D D , VASHUKOVA E S , BARBITOFF Y A , et al. Current status and prospects of the single-cell sequencing technologies for revealing the pathogenesis of pregnancy-associated disorders[J]. Genes (Basel), 2023, 14 (3): 756.
doi: 10.3390/genes14030756 |
10 |
LIU X Q , XU G , CHEN C S , et al. Evaluation of pulmonary single-cell identity specificity in scRNA-seq analysis[J]. Clin Transl Med, 2022, 12 (12): e1132.
doi: 10.1002/ctm2.1132 |
11 |
FENG M , SWEVERS L , SUN J C . Hemocyte clusters defined by scRNA-Seq in Bombyx mori: in silico analysis of predicted marker genes and implications for potential functional roles[J]. Front Immunol, 2022, 13, 852702.
doi: 10.3389/fimmu.2022.852702 |
12 |
LI X W , ZHANG Q , ZHU X C , et al. Standardization status of single-cell RNA sequencing technology in animal husbandry[J]. China Standardization, 2023, (1): 60- 64.
doi: 10.3969/j.issn.1002-5944.2023.01.006 |
13 |
TANG F C , BARBACIORU C , WANG Y Z , et al. mRNA-Seq whole-transcriptome analysis of a single cell[J]. Nat Methods, 2009, 6 (5): 377- 382.
doi: 10.1038/nmeth.1315 |
14 |
GRINDBERG R V , YEE-GREENBAUM J L , MCCONNELL M J , et al. RNA-sequencing from single nuclei[J]. Proc Natl Acad Sci U S A, 2013, 110 (49): 19802- 19807.
doi: 10.1073/pnas.1319700110 |
15 | 娄姬英, 郭其新, 毕瑜林, 等. 单细胞转录组测序技术及其在动物科学领域的应用[J]. 农业生物技术学报, 2023, 31 (5): 1074- 1087. |
LOU J Y , GUO Q X , BI Y L , et al. Single-cell transcriptome sequencing technology and its application in the field of animal science[J]. Journal of Agricultural Biotechnology, 2023, 31 (5): 1074- 1087. | |
16 |
KOLODZIEJCZYK A A , KIM J K , SVENSSON V , et al. The technology and biology of single-cell RNA sequencing[J]. Mol Cell, 2015, 58 (4): 610- 620.
doi: 10.1016/j.molcel.2015.04.005 |
17 |
康彦东, 王兴东, 郭韶珂, 等. 单细胞测序技术及其在畜牧科学研究中的应用[J]. 中国牛业科学, 2022, 48 (4): 41- 45.
doi: 10.3969/j.issn.1001-9111.2022.04.009 |
KANG Y D , WANG X D , GUO S K , et al. Single-cell sequencing technology and its application in animal science research[J]. China Cattle Science, 2022, 48 (4): 41- 45.
doi: 10.3969/j.issn.1001-9111.2022.04.009 |
|
18 | 易兰兰, 贺德勇, 许宏, 等. 单细胞转录组测序技术在动物肠道中的应用研究进展[J]. 饲料研究, 2023, 46 (11): 159- 163. |
YI L L , HE D Y , XU H , et al. Study progress of application of single-cell transcriptome sequencing technology in animal intestine[J]. Feed Research, 2023, 46 (11): 159- 163. | |
19 |
LI X L , GIBSON G , QIU P . Gene representation in scRNA-seq is correlated with common motifs at the 3' end of transcripts[J]. Front Bioinform, 2023, 3, 1120290.
doi: 10.3389/fbinf.2023.1120290 |
20 |
NIE X E , QIN D , ZHOU X Y , et al. Clustering ensemble in scRNA-seq data analysis: methods, applications and challenges[J]. Comput Biol Med, 2023, 159, 106939.
doi: 10.1016/j.compbiomed.2023.106939 |
21 |
THURMAN A L , RATCLIFF J A , CHIMENTI M S , et al. Differential gene expression analysis for multi-subject single-cell RNA-sequencing studies with aggregateBioVar[J]. Bioinformatics, 2021, 37 (19): 3243- 3251.
doi: 10.1093/bioinformatics/btab337 |
22 |
KHOZYAINOVA A A , VALYAEVA A A , ARBATSKY M S , et al. Complex analysis of single-cell RNA sequencing data[J]. Biochemistry (Mosc), 2023, 88 (2): 231- 252.
doi: 10.1134/S0006297923020074 |
23 | 彭巍, 贾可欣, 张子敬, 等. 单细胞测序技术及其在畜禽遗传育种中的应用研究新进展[J]. 中国畜牧杂志, 2022, 58 (10): 44- 49. |
PENG W , JIA K X , ZHANG Z J , et al. New progress on single cell sequencing technology and its application to animal genetics and breeding[J]. Chinese Journal of Animal Science, 2022, 58 (10): 44- 49. | |
24 | SINGH A, HERMANN B P. Bulk and single-cell RNA-Seq analyses for studies of spermatogonia[M]//OATLEY J M, HERMANN B P. Spermatogonial Stem Cells: Methods and Protocols. New York: Humana, 2023: 37-70. |
25 |
KRIŽANOVIĆ K , ECHCHIKI A , ROUX J , et al. Evaluation of tools for long read RNA-seq splice-aware alignment[J]. Bioinformatics, 2018, 34 (5): 748- 754.
doi: 10.1093/bioinformatics/btx668 |
26 |
XU L , XUE T , DING W Y , et al. Comparison of scRNA-seq data analysis method combinations[J]. Brief Funct Genomics, 2022, 21 (6): 433- 440.
doi: 10.1093/bfgp/elac027 |
27 |
STUART T , BUTLER A , HOFFMAN P , et al. Comprehensive integration of single-cell data[J]. Cell, 2019, 177 (7): 1888- 1902.e21.
doi: 10.1016/j.cell.2019.05.031 |
28 |
LI X T , ZHANG S X , WONG K C . Deep embedded clustering with multiple objectives on scRNA-seq data[J]. Brief Bioinform, 2021, 22 (5): bbab090.
doi: 10.1093/bib/bbab090 |
29 | CHOI Y H , KIM J K . Dissecting cellular heterogeneity using single-cell RNA sequencing[J]. Mol Cells, 2019, 42 (3): 189- 199. |
30 | GAO S. Data analysis in single-cell transcriptome sequencing[M]//HUANG T. Computational Systems Biology: Methods and Protocols. New York: Humana, 2018: 311-326. |
31 |
CHOUDHARY S , SATIJA R . Comparison and evaluation of statistical error models for scRNA-seq[J]. Genome Biol, 2022, 23 (1): 27.
doi: 10.1186/s13059-021-02584-9 |
32 | DONG X R, BACHER R. Analysis of single-cell RNA-seq data[M]//FRIDLEY B, WANG X F. Statistical Genomics. New York: Humana, 2023: 95-114. |
33 |
BOULAND G A , MAHFOUZ A , REINDERS M J T . Consequences and opportunities arising due to sparser single-cell RNA-seq datasets[J]. Genome Biol, 2023, 24 (1): 86.
doi: 10.1186/s13059-023-02933-w |
34 |
YIP S H , SHAM P C , WANG J W . Evaluation of tools for highly variable gene discovery from single-cell RNA-seq data[J]. Brief Bioinform, 2019, 20 (4): 1583- 1589.
doi: 10.1093/bib/bby011 |
35 |
ZHANG S Q , XIE L J , CUI Y X , et al. Detecting fear-memory-related genes from neuronal scRNA-seq data by diverse distributions and Bhattacharyya distance[J]. Biomolecules, 2022, 12 (8): 1130.
doi: 10.3390/biom12081130 |
36 |
SUN Y T , QIU P . Domain adaptation for supervised integration of scRNA-seq data[J]. Commun Biol, 2023, 6 (1): 274.
doi: 10.1038/s42003-023-04668-7 |
37 | LU S, KELEŞ S. Dozer: debiased personalized gene co-expression networks for population-scale scRNA-seq data[J]. bioRxiv, 2023. |
38 | 雷佩佩. 基于单细胞测序解析猪精原细胞的异质性[D]. 杨凌: 西北农林科技大学, 2021. |
LEI P P. The analysis of heterogeneity in porcine spermatogonia based on the single cell sequencing[D]. Yangling: Northwest A&F University, 2021. (in Chinese) | |
39 |
ZHANG L K , LI F Y , LEI P P , et al. Single-cell RNA-sequencing reveals the dynamic process and novel markers in porcine spermatogenesis[J]. J Anim Sci Biotechnol, 2021, 12 (1): 122.
doi: 10.1186/s40104-021-00638-3 |
40 |
张发利, 朱可心, 葛伟, 等. 猪与绵羊睾丸发育特征的单细胞转录组差异的比较分析[J]. 猪业科学, 2023, 40 (5): 106- 109.
doi: 10.3969/j.issn.1673-5358.2023.05.034 |
ZHANG F L , ZHU K X , GE W , et al. Comparative analysis of single-cell transcriptomic differences in testicular developmental characteristics between pigs and sheep[J]. Swine Industry Science, 2023, 40 (5): 106- 109.
doi: 10.3969/j.issn.1673-5358.2023.05.034 |
|
41 |
ZHANG L K , GUO M , LIU Z D , et al. Single-cell RNA-seq analysis of testicular somatic cell development in pigs[J]. J Genet Genomics, 2022, 49 (11): 1016- 1028.
doi: 10.1016/j.jgg.2022.03.014 |
42 |
ZHAO H , WU Z W , ZHANG R , et al. Dynamic changes of 3'UTR length during oocyte-to-zygote transition of in vitro pig embryos[J]. Reprod Domest Anim, 2023, 58 (5): 605- 613.
doi: 10.1111/rda.14327 |
43 | WIARDA J E , BECKER S R , SIVASANKARAN S K , et al. Regional epithelial cell diversity in the small intestine of pigs[J]. J Anim Sci, 2023, 101 (1): skac318. |
44 |
CAI S F , HU B , WANG X Y , et al. Integrative single-cell RNA-seq and ATAC-seq analysis of myogenic differentiation in pig[J]. BMC Biol, 2023, 21 (1): 19.
doi: 10.1186/s12915-023-01519-z |
45 |
XU D D , WAN B Y , QIU K , et al. Single-cell RNA-sequencing provides insight into skeletal muscle evolution during the selection of muscle characteristics[J]. Adv Sci (Weinh), 2023, 10 (35): e2305080.
doi: 10.1002/advs.202305080 |
46 |
ZHANG L J , ZHU J C , WANG H Y , et al. A high-resolution cell atlas of the domestic pig lung and an online platform for exploring lung single-cell data[J]. J Genet Genomics, 2021, 48 (5): 411- 425.
doi: 10.1016/j.jgg.2021.03.012 |
47 |
LI J , XU Y N , ZHANG J Y , et al. Single-cell transcriptomic analysis reveals transcriptional and cell subpopulation differences between human and pig immune cells[J]. Genes Genomics, 2024, 46 (3): 303- 322.
doi: 10.1007/s13258-023-01456-9 |
48 |
ZHENG Y X , LI S , LI S H , et al. Transcriptome profiling in swine macrophages infected with African swine fever virus at single-cell resolution[J]. Proc Natl Acad Sci U S A, 2022, 119 (19): e2201288119.
doi: 10.1073/pnas.2201288119 |
49 |
FAN B C , ZHOU J Z , ZHAO Y X , et al. Identification of cell types and transcriptome landscapes of porcine epidemic diarrhea virus-infected porcine small intestine using single-cell RNA sequencing[J]. J Immunol, 2023, 210 (3): 271- 282.
doi: 10.4049/jimmunol.2101216 |
50 | SUN C H , JIN K , ZUO Q S , et al. Characterization of alternative splicing (AS) events during chicken (Gallus gallus) male germ-line stem cell differentiation with single-cell RNA-seq[J]. Animals (Basel), 2021, 11 (5): 1469. |
51 | JUNG K M , SEO M , HAN J Y . Comparative single-cell transcriptomic analysis reveals differences in signaling pathways in gonadal primordial germ cells between chicken (Gallus gallus) and zebra finch (Taeniopygia guttata)[J]. Faseb J, 2023, 37 (1): e22706. |
52 |
CHOI H J , JUNG K M , PARK K J , et al. Single-cell transcriptome analysis of male chicken germ cells reveals changes in signaling pathway-related gene expression profiles during mitotic arrest[J]. FEBS Open Bio, 2023, 13 (5): 833- 844.
doi: 10.1002/2211-5463.13600 |
53 |
LI J H , XING S Y , ZHAO G P , et al. Identification of diverse cell populations in skeletal muscles and biomarkers for intramuscular fat of chicken by single-cell RNA sequencing[J]. BMC Genomics, 2020, 21 (1): 752.
doi: 10.1186/s12864-020-07136-2 |
54 |
MANTRI M , SCUDERI G J , ABEDINI-NASSAB R , et al. Spatiotemporal single-cell RNA sequencing of developing chicken hearts identifies interplay between cellular differentiation and morphogenesis[J]. Nat Commun, 2021, 12 (1): 1771.
doi: 10.1038/s41467-021-21892-z |
55 |
WU Z G , SHIH B , MACDONALD J , et al. Development and function of chicken XCR1+ conventional dendritic cells[J]. Front Immunol, 2023, 14, 1273661.
doi: 10.3389/fimmu.2023.1273661 |
56 |
QU X Y , LI X B , LI Z W , et al. Chicken peripheral blood mononuclear cells response to avian leukosis virus subgroup J infection assessed by single-cell RNA sequencing[J]. Front Microbiol, 2022, 13, 800618.
doi: 10.3389/fmicb.2022.800618 |
57 |
DAI M M , ZHU S F , AN Z H , et al. Dissection of key factors correlating with H5N1 avian influenza virus driven inflammatory lung injury of chicken identified by single-cell analysis[J]. PLoS Pathog, 2023, 19 (10): e1011685.
doi: 10.1371/journal.ppat.1011685 |
58 | 高源. 安格斯牛睾丸组织非编码RNA鉴定及单细胞转录图谱绘制[D]. 杨凌: 西北农林科技大学, 2021. |
GAO Y. Non-coding RNA identification and single-cell transcriptome atlas of angus bull testis[D]. Yangling: Northwest A&F University, 2021. (in Chinese) | |
59 | YANG H , MA J Y , WAN Z , et al. Characterization of sheep spermatogenesis through single-cell RNA sequencing[J]. Faseb J, 2021, 35 (2): e21187. |
60 |
SU J , SONG Y L , YANG Y Y , et al. Study on the changes of LHR, FSHR and AR with the development of testis cells in Hu sheep[J]. Anim Reprod Sci, 2023, 256, 107306.
doi: 10.1016/j.anireprosci.2023.107306 |
61 | 苏杰. 出生后湖羊睾丸发育图谱、组织结构及X染色体剂量补偿研究[D]. 呼和浩特: 内蒙古农业大学, 2022. |
SU J. Studies on testis development atlas, structure and X-chromosome dose compensation after Hu sheep birth[D]. Hohhot: Inner Mongolia Agricultural University, 2022. (in Chinese) | |
62 |
YU X W , LI T T , DU X M , et al. Single-cell RNA sequencing reveals atlas of dairy goat testis cells[J]. Zool Res, 2021, 42 (4): 401- 405.
doi: 10.24272/j.issn.2095-8137.2020.373 |
63 |
JIA G X , MA W J , WU Z B , et al. Single-cell transcriptomic characterization of sheep conceptus elongation and implantation[J]. Cell Rep, 2023, 42 (8): 112860.
doi: 10.1016/j.celrep.2023.112860 |
64 |
CAI C C , WAN P , WANG H , et al. Transcriptional and open chromatin analysis of bovine skeletal muscle development by single-cell sequencing[J]. Cell Prolif, 2023, 56 (9): e13430.
doi: 10.1111/cpr.13430 |
65 | 叶娜. 基于单细胞转录组测序对天祝白牦牛生长期毛囊转录图谱的构建[D]. 兰州: 西北民族大学, 2021. |
YE N. Construction of transcription map of hair follicles in growing period of Tianzhu white yak based on single cell transcriptome sequencing[D]. Lanzhou: Northwest Minzu University, 2021. (in Chinese) | |
66 |
张卫东, 郑玉杰, 葛伟, 等. 单细胞测序对绒山羊毛乳头细胞的鉴定[J]. 中国农业科学, 2022, 55 (12): 2436- 2446.
doi: 10.3864/j.issn.0578-1752.2022.12.014 |
ZHANG W D , ZHENG Y J , GE W , et al. Identification of cashmere dermal papilla cells based on single-cell RNA sequencing technology[J]. Scientia Agricultura Sinica, 2022, 55 (12): 2436- 2446.
doi: 10.3864/j.issn.0578-1752.2022.12.014 |
|
67 | 刘泽昊. 单细胞测序解析辽宁绒山羊初级与次级毛囊的转录组图谱与分子特征[D]. 沈阳: 沈阳农业大学, 2022. |
LIU Z H. Single-cell sequencing reveals that transcriptome map and molecular features of primary and secondary hair follicles in Liaoning cashmere goats[D]. Shenyang: Shenyang Agricultural University, 2022. (in Chinese) | |
68 | 葛伟. 单细胞分辨率解析绒山羊及小鼠毛囊发生的转录调控机制[D]. 杨凌: 西北农林科技大学, 2019. |
GE W. Dissecting the transcriptional regulatory mechanism underlying cashmere goat and murine hair follicle morphogenesis at single-cell resolution[D]. Yangling: Northwest A&F University, 2019. (in Chinese) | |
69 |
WANG S H , WU T Y , SUN J Y , et al. Single-cell transcriptomics reveals the molecular anatomy of sheep hair follicle heterogeneity and wool curvature[J]. Front Cell Dev Biol, 2021, 9, 800157.
doi: 10.3389/fcell.2021.800157 |
70 | HE T Y , GUO W R , YANG G , et al. A single-cell atlas of an early mongolian sheep embryo[J]. Vet Sci, 2023, 10 (9): 543. |
71 | 何亭漪. 单细胞转录组测序分析呼伦贝尔草原短尾羊和乌珠穆沁羊16天胚胎的基因表达差异[D]. 呼和浩特: 内蒙古农业大学, 2021. |
HE T Y. Single-cell transcriptome sequencing analyses the gene expression differences in 16-day embryos of HulunBuir short-tailed sheep and Ujumqin sheep[D]. Hohhot: Inner Mongolia Agricultural University, 2021. (in Chinese) | |
72 |
YUAN Y , SUN D M , QIN T , et al. Single-cell transcriptomic landscape of the sheep rumen provides insights into physiological programming development and adaptation of digestive strategies[J]. Zool Res, 2022, 43 (4): 634- 647.
doi: 10.24272/j.issn.2095-8137.2022.086 |
73 |
DENG J , LIU Y J , WEI W T , et al. Single-cell transcriptome and metagenome profiling reveals the genetic basis of rumen functions and convergent developmental patterns in ruminants[J]. Genome Res, 2023, 33 (10): 1690- 1707.
doi: 10.1101/gr.278239.123 |
74 | 寇佳怡. 黄牛肺脏单细胞转录图谱的构建及初步分析[D]. 成都: 西南民族大学, 2022. |
KOU J Y. Construction and preliminary analysis of single cell transcriptional map in the lung of cattle[D]. Chengdu: Southwest Minzu University, 2022. (in Chinese) | |
75 | BARUT G T , KREUZER M , BRUGGMANN R , et al. Single-cell transcriptomics reveals striking heterogeneity and functional organization of dendritic and monocytic cells in the bovine mesenteric lymph node[J]. Front Immunol, 2022, 13, 1099357. |
76 |
HUANG K L , YANG B , XU Z B , et al. The early life immune dynamics and cellular drivers at single-cell resolution in lamb forestomachs and abomasum[J]. J Anim Sci Biotechnol, 2023, 14 (1): 130.
doi: 10.1186/s40104-023-00933-1 |
77 | 杜源. 单细胞组学联合细胞示踪技术探究细胞移植再生肝脏的机制[D]. 南昌: 南昌大学, 2023. |
DU Y. Unveiling the mechanisms of liver regeneration by hepatocyte transplantation using cell tracing and single-cell RNA sequencing[D]. Nanchang: Nanchang University, 2023. (in Chinese) | |
78 |
ZENG H , HUANG J H , REN J Y , et al. Spatially resolved single-cell translatomics at molecular resolution[J]. Science, 2023, 380 (6652): eadd3067.
doi: 10.1126/science.add3067 |
79 |
YI Q J , WANG J , LIU T T , et al. scRNA-Seq and imaging mass cytometry analyses unveil iNKT cells-mediated anti-tumor immunity in pancreatic cancer liver metastasis[J]. Cancer Lett, 2023, 561, 216149.
doi: 10.1016/j.canlet.2023.216149 |
80 |
WANG L W , LIU Y H , DAI Y T , et al. Single-cell RNA-seq analysis reveals BHLHE40-driven pro-tumour neutrophils with hyperactivated glycolysis in pancreatic tumour microenvironment[J]. Gut, 2023, 72 (5): 958- 971.
doi: 10.1136/gutjnl-2021-326070 |
81 |
LI H N , WANG X D , WANG Y L , et al. Cross-species single-cell transcriptomic analysis reveals divergence of cell composition and functions in mammalian ileum epithelium[J]. Cell Regen, 2022, 11 (1): 19.
doi: 10.1186/s13619-022-00118-7 |
82 |
XIONG Z H , LUO J W , SHI W W , et al. scGCL: an imputation method for scRNA-seq data based on graph contrastive learning[J]. Bioinformatics, 2023, 39 (3): btad098.
doi: 10.1093/bioinformatics/btad098 |
83 |
WU W M , ZHANG W S , HOU W M , et al. Multi-view clustering with graph learning for scRNA-Seq data[J]. IEEE/ACM Trans Comput Biol Bioinform, 2023, 20 (6): 3535- 3546.
doi: 10.1109/TCBB.2023.3298334 |
84 |
ZAPPIA L , PHIPSON B , OSHLACK A . Exploring the single-cell RNA-seq analysis landscape with the scRNA-tools database[J]. PLoS Comput Biol, 2018, 14 (6): e1006245.
doi: 10.1371/journal.pcbi.1006245 |
85 | 汪浩浩, 陈庆杰, 刘清华, 等. 单细胞RNA测序技术及其在医学研究中的应用[J]. 医学研究杂志, 2023, 1- 7. |
WANG H H , CHEN Q J , LIU Q H , et al. Single-cell RNA sequencing technology and its application in medical research[J]. Journal of Medical Research, 2023, 1- 7. |
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