单细胞circRNA初步了解

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前面我们系统性地总结了circRNA的相关背景知识：

  • 首先了解一下circRNA背景知识
  • circRNA芯片分析的一般流程
  • circRNA-seq分析的一般流程
  • ceRNA-芯片分析的一般流程
  • circRNA_ID转化
    但都是基于大量细胞的，而我们是单细胞天地平台，有必要也系统性探索一下单细胞circRNA技术的进展。

    single-cell universal poly(A)-independent RNA sequencing (SUPeR-seq)

    谷歌能搜索到的单细胞circRNA技术最早应该是Published: 23 July 2015的文章Single-cell RNA-seq transcriptome analysis of linear and circular RNAs in mouse preimplantation embryos 发表在Genome Biology 杂志，这个杂志发表了不少NGS相关测序技术的文章。是北京大学光学中心黄岩宜教授的团队出品，因为circRNA技术领域本身没有RNA本身应用广泛，所以这个SUPeR-seq技术到现在（2020-01-05 ），也就150多个引用而已。
    里面提到：We identified 696 poly(A)- genes by bulk RNA sequencing, of which around 30 % could be recovered in a single cell by SUPeR-seq 有相关课题的朋友可以深入阅读，其数据分析流程是：

  • 1.Raw data from illumina Hiseq2000 or Hiseq2500
  • 2.Quality control (QC): cut adaptor and low quality reads
  • 3.Map to genome: using TopHat2 default setting
  • 4.Output unmapped reads: using Samtools view -f 4
  • 5.Create anchor reads: cut 25 bp from two ends of each 100 bp read
  • 6.Map anchor reads to genome: using Bowtie2 default setting
  • 7.Filter candidate reads: find sequence with two anchors mapping to the same chromsome of opposite directions within distance <200 kb
  • 8.Filtering with existing exon junctions: the two anchors of candidate circRNA reads are then mapped to the exons within the same transcript and they must match the flanking sequences of exons.

    　单细胞水平评价circRNA检测软件性能

    我在circRNA-seq分析的一般流程提到过2015年12月10日发表在《Nucleic Acid Research》 的 https://www.ncbi.nlm.nih.gov/pubmed/26657634 ，文献提到的5种算法预测得到的结果差别较大，而且有很高的假阳性。单细胞水平同样的也可以看不同算法的差异，比如发表于Published: 31 October 2017 在Scientific Reports volume杂志的文章：Heterogeneous circRNA expression profiles and regulatory functions among HEK293T single cells，就对研究者自己的数据集 GSE78968 had 38 single cells, 使用了 CIRI2, circRNAFinder, find_circ and CIRCexplorer这４个软件，看看他们的效果。

    The number of circRNAs ranged from 1,111 to 6,493 in 38 single cells, in which only 410 circRNAs were predicted by all the four methods.
    研究者还测试了 GSE53386 数据集(7 single HEK293T cells,)里面的单细胞circRNA检测情况，同样是4个软件的比较。
    其它类似的文献也有：https://www.biorxiv.org/content/10.1101/430090v1.full

    如果你也想做单细胞水平的circRNA研究

    这个SUPeR-seq技术应该是比较难掌握，可能得去北京大学光学中心黄岩宜教授那边学习，这个研究领域确实很新，是机遇，但是没有实力也请三思。
    其它文献推荐：

  • Front. Plant Sci., 02 April 2019 | https://doi.org/10.3389/fpls.2019.00379 综述：Present Scenario of Circular RNAs (circRNAs) in Plants
  • 2018年5月 DOI: 10.1016/j.mad.2018.05.001 文章：CircRNA accumulation: A new hallmark of aging?
  • Published 29 March 2019. DOI: 10.26508/lsa.201900354 的研究：Sequence and expression levels of circular RNAs in progenitor cell types during mouse corticogenesis
  • EMBO J (2019)38:e100836https://doi.org/10.15252/embj.2018100836的综述：Past, present, and future of circRNAs
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