題目：《綜合單細(xì)胞異質(zhì)性分析方法來定義人類心臟核心轉(zhuǎn)錄因子層次結(jié)構(gòu)》

截止2019-10月引用率6次亏钩！

摘要

誘導(dǎo)人多能干細(xì)胞分化為心肌細(xì)胞（hiPSC-CMs）的技術(shù)已成為相關(guān)疾病建模和治療測試的有力工具镀裤。然而崭庸，由于不成熟和異質(zhì)性的的存在使得推廣仍然受到的限制智厌。為了闡明這種異質(zhì)性的原因虚茶，作者在hiPSC心肌誘導(dǎo)分化和成人心臟組織細(xì)胞中應(yīng)用了單細(xì)胞轉(zhuǎn)錄組和常規(guī)轉(zhuǎn)錄組測序技術(shù)讨阻。通過整合及拼接數(shù)據(jù)等分析料按，觀察到了超過六個(gè)的不同單細(xì)胞亞群，其中幾群細(xì)胞在分化的某個(gè)時(shí)間點(diǎn)（第30天不同）被重復(fù)觀測到瞬内。為了剖析與每個(gè)細(xì)胞群相關(guān)的不同心臟核心轉(zhuǎn)錄因子的調(diào)控作用迷雪，本文使用了single-cell 和 bulk RNA-seq、CRISPR技術(shù)虫蝶、ChIP-seq章咧，同時(shí)配合電生理、鈣成像和CyTOF分析檢測到三個(gè)轉(zhuǎn)錄因子（NR2F2能真、TBX5和HEY2）的上調(diào)或下調(diào)產(chǎn)生的影響赁严。匯總這些靶標(biāo)扰柠、數(shù)據(jù)和基因組分析方法為理解體外細(xì)胞異質(zhì)性提供了一個(gè)強(qiáng)大的平臺(tái)。

首先是樣品疼约，建庫測序卤档，RNA-seq上游分析概況

樣品來源

• Two hiPSC lines were obtained from the Stanford Cardiovascular Institute biobank (CVI0076, CVI0059). CVI0059 was processed for single cell RNA-seq at day 5, day 14, and day 45 of the cardiomyocyte differentiation protocol using the 10X Genomics single-cell RNA-seq v1 kit.CVI0076 was processed for single cell RNA-seq at day 0, day 5, day 14, and day 45 use v2 kit.
• Libraries were quantified using Bioanalyzer (Agilent) and qPCR (KAPA) analysis. Libraries were sequenced on the NextSeq 500 (Illumina).
• Unsupervised cell population discovery analyses were performed with Seurat-CCA and the software ICGS available in AltAnalyze version 2.1.1 (http://www.altanalyze.org)
• For these analyses, only protein-coding genes were considered, applying a correlation cutoff of 0.3 and Euclidean column HOPACH clustering. Associated t-SNE visualizations were obtained in AltAnalyze using ICGS obtained dynamically regulated genes.
• ERCC spike-ins were included for further evaluation of sample quality.
• libraries were pooled and sequenced using Illumina’s HiSeq 2000 using 2 × 100 paired-end sequencing (Macrogen, South Korea)
• Filtered reads were aligned to the reference genome hg19 using STAR
• Using STAR BAM files, AltAnalyze was used to generate exon read counts for gene expression analysis and junction read counts for splicing analysis
• All retained single-cell libraries were required to have a minimum of 1 million uniquely aligning paired-end fragments and > 40% aligned fragments, based on STAR analysis. The retained libraries had an average of ~3 million aligned fragments.
• To calculate RPKM values for each gene, AltAnalyze was run on the junction and exon BED files using default settings
• To identify discrete cell states, unsupervised clustering was initially performed to define predominant populations (ICGS module of AltAnalyze, Pearson correlation coefficient > 0.4).
• Although this analysis identified three initial populations, we augmented these results using a supervised analysis of cardiac transcription factors from our 10X Genomics identified using the ICGS supervised correlation option.
• In agreement with our Fluidigim C1 microscopy analyses, no gene expression signatures with evident “doublet cell” profiles (more than one cell population signature) were discerned from this analysis.
• Furthermore, ERCC spike-in expression (ERCC92.fa, Kallisto TPM) ratios indicated single-cell transcriptome profiles were being assessed.
• the MarkerFinder algorithm in AltAnalyze was run to identify additional genes with population- restricted expression profiles (Pearson correlation coefficient > 0.4).
• Additional differentiations were performed on NR2F2GE1 (N = 2), TBX5GE1 (N = 2), HEY2GE1 (N = 2), NR2F2GE2 (N = 4), TBX5GE2 (N = 3), and HEY2GE2 (N = 2) lines and sequenced using Illumina’s HiSeq 4000 2 × 150 paired end sequencing (Novogene).
• Pseudotemporal ordering of these cells with the software Monocle designated SF1-expressing cardiomyocytes as the “earliest” population and HOPX as the latest, suggesting that cardiomyocyte subpopulations underlie distinct cardiac maturation states
• Data availability
  GSE81585;
  10x Genomics synapse ID: syn7818379.

然后是質(zhì)量控制情況，最后的表達(dá)矩陣是多少個(gè)基因多少個(gè)細(xì)胞

• 200 hiPSC-CMs at day 30 were run throuth Fluidigm C1 microfluidic chip to capture single hiPSC-CMs (site 8shown) and processed for single-cell RNA-seq.
• Cells were labeled using a viability dye(Calcein-AM) to ensure RNA for live cells were processed. IHC TNNT2,MYL2,ACTC1,MYL7 marker
• 54 hiPSC-CMs were successfully sequenced which expressed cardiac markers
• single cell 10X genomics RNA-seq clusters called transcription factor and GO terms related to cardiac developmental progression
• Monocle applied to single- cell RNA-seq was used to identify a pseudotime progression of different populations of hiPSC-CMs in relation to each other.

接著介紹作者是如何挑選重要的基因和降維

• To visualize and interpret the high- dimensional dataset generated, we applied the t-SNE algorithm based on seven cardiac markers preselected for the dataset, in which individual cells in the high-dimensional space were pro- jected onto a two-dimensional map but their neighboring rela- tionship was preserved.

  
  
  Heatmap of gene markers specific for each day of differentiation. Selected cardiac specific genes are overlaid in the right panel.

降維后的聚類以及對每個(gè)類的注釋

tSNE聚類后注釋

與bulk RNA 測序得到的 基因marker進(jìn)行重新注釋分組

Single cells from day 30 of differentiation were profiled using an independent technology (Fluidigm C1) to resolve coincident mid-to-late state differentiation heterogeneity.

PCA聚類Single-cell population-specific genes(ICGS/MarkerFinder) and expression profiles were used to populate the LineageProfiler signature database

Evaluation of single-cell population heterogeneity among replicate bulk time-course samples is preformed using K-nearest neghbor-based classification of bulk RNA-seq time-course samples with the software LineageProfiler

Overlay of tSNE maps of cardiomyocytes derived from hESCs undergoing cardiac differentiation from day 8 to day 18 to day 30.Each point represents a single cell, and different colors represent samples from different colors represent samples from different time points.

An extended panel of relevant cardiac marker expression patterns.cells are colored based on the intensity of expression of the indicated markers. Higher expression of MLC2A was noted throughout each time point of differentiation, whereas high levels of MLC2V could only be observed at day 30

Bulk RNA seq: RNA-seq expression from each day of differentiation was analyzed for transcription factors demonstration a greater than two-fold change in expression from each day. A two-fold increase in expression was denoted as the start of transcription factor expression, whereas the corresponding two-fold decrease in expression was denoted as acessation of expression.

類的下游分析(差異分析或者實(shí)驗(yàn)驗(yàn)證等)

Chip-seq 驗(yàn)證 marker基因

類的差異基因分析

• Given that our single-cell RNA-seq of the wildtype and genome-edited lines suggested that NR2F2, TBX5, and HEY2 can regulate atrial-like and ventricular-like signatures, we next quantified the expression of these transcription factors within the adult heart
• RNA-seq of the human atria confirmed that NR2F2 and TBX5 are specifically enriched within the atria, and HEY2 is highly enriched within the ventricle.(Supplementary Fig. 5E).
• RNA-seq quantification demonstrated that MYL2 is highly expressed within ventricular tissue, while MYL7 is enriched within atrial tissue(Supplementary Fig. 5F).

• differentiating hiPSC-CMs reveals that MYL2 is only observed at later differentiation time points (e.g. day 30 and day 90) (Supplementary Fig. 5G).

  
  
  supFigure5

總結(jié)一下

• 本文作者通過對human embryonic stem cell-derived cardiomyocytes (hESC-CMs) 以及 human induced pluripotent stem cell-derived cardiomyocytes (hiPSC- CMs)取不同時(shí)間點(diǎn)及相應(yīng)的轉(zhuǎn)錄因子上調(diào)下調(diào)表達(dá)后選取特定時(shí)間的樣本進(jìn)行single-cell 和 bulk RNA-seq的分析程剥，確定了由不同基因表達(dá)譜富集的hiPSC-CM的亞種群劝枣。意義是由于心肌細(xì)胞的再生性差，損傷修復(fù)較困難织鲸，而且受損后嚴(yán)重危害人群健康舔腾，科學(xué)家們研究了hiPSC- CMs來治療心肌損傷，但是hiPSC- CMs自身的混雜導(dǎo)致了預(yù)后的異質(zhì)性搂擦，因此本文用單細(xì)胞測序的技術(shù)找到這個(gè)混雜的干細(xì)胞分化的的心肌細(xì)胞的特殊分化時(shí)期亞型所高表達(dá)的細(xì)胞標(biāo)記基因稳诚，從而實(shí)現(xiàn)分類富集相應(yīng)的亞群的心肌細(xì)胞，降低混雜差異提高治療效果非常值得期待瀑踢。