ReadZS detects cell type-specific and developmentally regulated RNA processing programs in single-cell RNA-seq

被引:3
|
作者
Meyer, Elisabeth [1 ,2 ]
Chaung, Kaitlin [1 ,2 ]
Dehghannasiri, Roozbeh [1 ,2 ]
Salzman, Julia [1 ,2 ,3 ]
机构
[1] Stanford Univ, Dept Biochem, Stanford, CA 94305 USA
[2] Stanford Univ, Dept Biomed Data Sci, Stanford, CA 94305 USA
[3] Stanford Univ, Dept Stat Courtesy, Stanford, CA 94305 USA
基金
美国国家科学基金会;
关键词
scRNA-seq; Differential RNA processing; Alternative polyadenylation; Untranslated regions; 3' UNTRANSLATED REGIONS; ALTERNATIVE POLYADENYLATION; MESSENGER-RNAS; GREATWALL;
D O I
10.1186/s13059-022-02795-8
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
RNA processing, including splicing and alternative polyadenylation, is crucial to gene function and regulation, but methods to detect RNA processing from single-cell RNA sequencing data are limited by reliance on pre-existing annotations, peak calling heuristics, and collapsing measurements by cell type. We introduce ReadZS, an annotation-free statistical approach to identify regulated RNA processing in single cells. ReadZS discovers cell type-specific RNA processing in human lung and conserved, developmentally regulated RNA processing in mammalian spermatogenesis-including global 3 ' UTR shortening in human spermatogenesis. ReadZS also discovers global 3 ' UTR lengthening in Arabidopsis development, highlighting the usefulness of this method in under-annotated transcriptomes.
引用
收藏
页数:28
相关论文
共 50 条
  • [31] Guidelines for reporting single-cell RNA-seq experiments
    Fullgrabe, Anja
    George, Nancy
    Green, Matthew
    Nejad, Parisa
    Aronow, Bruce
    Fexova, Silvie Korena
    Fischer, Clay
    Freeberg, Mallory Ann
    Huerta, Laura
    Morrison, Norman
    Scheuermann, Richard H.
    Taylor, Deanne
    Vasilevsky, Nicole
    Clarke, Laura
    Gehlenborg, Nils
    Kent, Jim
    Marioni, John
    Teichmann, Sarah
    Brazma, Alvis
    Papatheodorou, Irene
    NATURE BIOTECHNOLOGY, 2020, 38 (12) : 1384 - 1386
  • [32] Single-cell RNA-seq: advances and future challenges
    Saliba, Antoine-Emmanuel
    Westermann, Alexander J.
    Gorski, Stanislaw A.
    Vogel, Joerg
    NUCLEIC ACIDS RESEARCH, 2014, 42 (14) : 8845 - 8860
  • [33] A SMARTer solution to stranded single-cell RNA-seq
    Gandlur, S.
    Pesant, M.
    Bolduc, N.
    Lee, S.
    Hardy, C.
    Das, A.
    Bostick, M.
    Farmer, A.
    EUROPEAN JOURNAL OF HUMAN GENETICS, 2019, 27 : 1716 - 1717
  • [34] Practical Compass of Single-Cell RNA-Seq Analysis
    Okada, Hiroyuki
    Chung, Ung-il
    Hojo, Hironori
    CURRENT OSTEOPOROSIS REPORTS, 2024, 22 (05) : 433 - 440
  • [35] Embracing the dropouts in single-cell RNA-seq analysis
    Peng Qiu
    Nature Communications, 11
  • [36] Evaluation of Cell Type Annotation R Packages on Single-cell RNA-seq Data
    Huang, Qianhui
    Liu, Yu
    Du, Yuheng
    Garmire, Lana X.
    GENOMICS PROTEOMICS & BIOINFORMATICS, 2021, 19 (02) : 267 - 281
  • [37] How deep is enough in single-cell RNA-seq?
    Aaron M Streets
    Yanyi Huang
    Nature Biotechnology, 2014, 32 : 1005 - 1006
  • [38] Guidelines for reporting single-cell RNA-seq experiments
    Anja Füllgrabe
    Nancy George
    Matthew Green
    Parisa Nejad
    Bruce Aronow
    Silvie Korena Fexova
    Clay Fischer
    Mallory Ann Freeberg
    Laura Huerta
    Norman Morrison
    Richard H. Scheuermann
    Deanne Taylor
    Nicole Vasilevsky
    Laura Clarke
    Nils Gehlenborg
    Jim Kent
    John Marioni
    Sarah Teichmann
    Alvis Brazma
    Irene Papatheodorou
    Nature Biotechnology, 2020, 38 : 1384 - 1386
  • [39] Single-cell RNA-Seq unveils tumor microenvironment
    Lee, Hae-Ock
    Park, Woong-Yang
    BMB REPORTS, 2017, 50 (06) : 283 - 284
  • [40] From single-cell RNA-seq to transcriptional regulation
    Gioele La Manno
    Nature Biotechnology, 2019, 37 : 1421 - 1422