Evolutionary analysis reveals regulatory and functional landscape of coding and non-coding RNA editing

被引:56
作者
Zhang, Rui [1 ,2 ]
Deng, Patricia [1 ]
Jacobson, Dionna [1 ]
Li, Jin Billy [1 ]
机构
[1] Stanford Univ, Dept Genet, Stanford, CA 94305 USA
[2] Sun Yat Sen Univ, Sch Life Sci, State Key Lab Biocontrol, Guangzhou 510275, Guangdong, Peoples R China
来源
PLOS GENETICS | 2017年 / 13卷 / 02期
基金
美国国家卫生研究院; 美国国家科学基金会; 中国国家自然科学基金;
关键词
DROSOPHILA; SITES; IDENTIFICATION; ADENOSINES; MUTATION; GENES;
D O I
10.1371/journal.pgen.1006563
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Adenosine-to-inosine RNA editing diversifies the transcriptome and promotes functional diversity, particularly in the brain. A plethora of editing sites has been recently identified; however, how they are selected and regulated and which are functionally important are largely unknown. Here we show the cis-regulation and stepwise selection of RNA editing during Drosophila evolution and pinpoint a large number of functional editing sites. We found that the establishment of editing and variation in editing levels across Drosophila species are largely explained and predicted by cis-regulatory elements. Furthermore, editing events that arose early in the species tree tend to be more highly edited in clusters and enriched in slowly-evolved neuronal genes, thus suggesting that the main role of RNA editing is for fine-tuning neurological functions. While nonsynonymous editing events have been long recognized as playing a functional role, in addition to nonsynonymous editing sites, a large fraction of 3'UTR editing sites is evolutionarily constrained, highly edited, and thus likely functional. We find that these 3'UTR editing events can alter mRNA stability and affect miRNA binding and thus highlight the functional roles of noncoding RNA editing. Our work, through evolutionary analyses of RNA editing in Drosophila, uncovers novel insights of RNA editing regulation as well as its functions in both coding and non-coding regions.
引用
收藏
页数:24
相关论文
共 57 条
  • [51] ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data
    Wang, Kai
    Li, Mingyao
    Hakonarson, Hakon
    [J]. NUCLEIC ACIDS RESEARCH, 2010, 38 (16) : e164
  • [52] Xu G, 2014, MOL BIOL EVOLUTION
  • [53] Human coding RNA editing is generally nonadaptive
    Xu, Guixia
    Zhang, Jianzhi
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2014, 111 (10) : 3769 - 3774
  • [54] The molecular link between inefficient G1uA2 Q/R site-RNA editing and TDP-43 pathology in motor neurons of sporadic amyotrophic lateral sclerosis patients
    Yamashita, Takenari
    Kwak, Shin
    [J]. BRAIN RESEARCH, 2014, 1584 : 28 - 38
  • [55] PAML 4: Phylogenetic analysis by maximum likelihood
    Yang, Ziheng
    [J]. MOLECULAR BIOLOGY AND EVOLUTION, 2007, 24 (08) : 1586 - 1591
  • [56] The Landscape of A-to-I RNA Editome Is Shaped by Both Positive and Purifying Selection
    Yu, Yao
    Zhou, Hongxia
    Kong, Yimeng
    Pan, Bohu
    Chen, Longxian
    Wang, Hongbing
    Hao, Pei
    Li, Xuan
    [J]. PLOS GENETICS, 2016, 12 (07):
  • [57] Quantifying RNA allelic ratios by microfluidic multiplex PCR and sequencing
    Zhang, Rui
    Li, Xin
    Ramaswami, Gokul
    Smith, Kevin S.
    Turecki, Gustavo
    Montgomery, Stephen B.
    Li, Jin Billy
    [J]. NATURE METHODS, 2014, 11 (01) : 51 - +