臺灣博碩士論文加值系統

微型核糖核酸(microRNA; miRNA)是一種非編碼之核糖核酸，透過切斷目標信息
核醣核酸(Messenger RNA; mRNA)，來達到抑制基因表現量之功能。由於高通量
之小型核醣核酸測序(Small RNA-Seq)和核糖核酸測序(RNA-Seq)之平台，讓我們
可以更了解miRNA 和mRNA 在全基因體內之分布與表現量多寡。實際上，被
miRNA 切斷之mRNA 於被降解前仍會存在細胞內一段時間。這些被切斷之殘存
序列，仍可能被現有定序平台偵測到，造成在切位附近的mRNA 表現量有所異
常。本篇論文發展出一套統計方法，能結合RNA-seq 與切位資訊，偵測出因
miRNA 切斷所造成之異常mRNA 表現，更準確地偵測出miRNA-mRNA 交互作
用。我們的方法應用在二種水稻品種之耐寒研究。我們從分析不同水稻品種之
small RNA-seq 與RNA-seq，鑑定出23 miRNA-mRNA 交互作用，可能與耐寒成
因有高度相關性。

MicroRNAs (miRNAs) are noncoding small RNAs which suppress target mRNA expres-
sion by cleavage. Thanks to the development of small RNA sequencing (small RNA-Seq)
and RNA sequencing (RNA-Seq), we can gain insight into the landscape and expres-
sion abundance of miRNAs and mRNAs in the genome. In reality, the miRNA-cleaved
transcripts remain in the cell before degradation. These cleaved transcripts may be still
captured and sequenced, leading to aberrant expression around the cleavage site. In
this thesis, we design and implement a statistical framework for identifying aberrant
expression caused by miRNA cleavage from RNA-seq. Our method is applied on a cold-
stress study of two rice strains. We identied 23 miRNA-mRNA interactions with such
aberrant expression, which are highly correlated to tolerance of cold stress.

Abstract i
Acknowledgements ii
List of Figures v
List of Tables vii
1 Introduction 1
2 Literature Review 3
2.1 RNA Sequencing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2.2 Small RNA sequencing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.3 Cleavage site . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.4 Chi-square test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.4.1 Goodness of Fit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.5 T-test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.5.1 Paired T-test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.5.2 Two-sample T-test . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.5.2.1 Equal sample sizes, equal variance . . . . . . . . . . . . . 5
2.5.2.2 Unequal sample sizes, equal variance . . . . . . . . . . . . 6
2.5.2.3 Equal or Unequal sample sizesm unequal variances . . . . 6
3 Material and Method 7
3.1 Material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
3.2 Mapping of RNA-seq Reads . . . . . . . . . . . . . . . . . . . . . . . . . . 8
3.3 Preprocess and Prediction of miRNAs from small RNA-seq . . . . . . . . 8
3.4 miRNA Target Prediction . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
3.5 Normalization of miRNA and Transcript Expression . . . . . . . . . . . . 9
3.6 Filtration of low expression transcripts and sampling for rescale . . . . . . 11
3.6.1 Filtration of low expression transcripts . . . . . . . . . . . . . . . . 11
3.6.2 Sampling for rescale . . . . . . . . . . . . . . . . . . . . . . . . . . 11
3.7 Detecting dierential expression with coverage bias . . . . . . . . . . . . . 12
3.7.1 The coverage bias of sequencing result . . . . . . . . . . . . . . . . 12
3.7.2 Detecting dierential expression at 5' end . . . . . . . . . . . . . . 13
3.8 Correction of cleavage-induced coverage bias . . . . . . . . . . . . . . . . . 14
3.8.1 5' end expression greater than 3' end . . . . . . . . . . . . . . . . . 15
3.8.2 Low expression at 5' end . . . . . . . . . . . . . . . . . . . . . . . . 16
4 Results and Discussion 18
4.1 miRNA-RNA Interactions Identied from miRNA-seq and RNA-seq . . . 18
4.2 miRNA-RNA Interactions found with known miRNAs . . . . . . . . . . . 18
4.3 Candidates comparison between known and prediction of miRNAs . . . . 19
4.4 Correlation between miRNA cleavage and rice
owering . . . . . . . . . . 21
5 Discussion, Conclusion and Future Work 22
5.1 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
5.2 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
5.3 Future work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
A The Candidates of Result from Predicted miRNAs 24
B The Candidates of Result from Known miRNAs 32
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