Generation and Bioinformatic Analysis of Synthetic Ago HITS-CLIP Data

34 Pages·2013·1.89 MB·English

IT 13 039
Examensarbete 45 hp
Juni 2013
Generation and Bioinformatic
Analysis of Synthetic Ago HITS-CLIP
Data
Mehmet Ali Arslan
Institutionen för informationsteknologi
Department of Information Technology

Abstract
Generation and Bioinformatic Analysis of Synthetic
Ago HITS-CLIP Data
Mehmet Ali Arslan

Teknisk- naturvetenskaplig fakultet
UTH-enheten Micro-RNAs (miRNAs) have been discovered to
regulate messenger RNA (mRNA) translation and
Besöksadress: degradation. Various recent studies have been focused
Ångströmlaboratoriet
on miRNA target prediction, in order to get a better
Lägerhyddsvägen 1
Hus 4, Plan 0 understanding of the rules and nature of miRNA
regulation over mRNAs. In this project we aim to
Postadress: create a software module to identify miRNA target
Box 536
sites on mRNAs. As basis to this project, we refer to a
751 21 Uppsala
study that identified a platform for miRNA-mRNA

Telefon: interaction in protein-RNA complexes in mouse brain
018 – 471 30 03 (AGO HITS-CLIP study). We propose a probabilistic
model of the data from this study, and generate
Telefax:
synthetic sample data according to this model, in
018 – 471 30 00
order to create a test bed for a discovery module. Our
Hemsida: discovery module analyzes the sample data to identify

http://www.teknat.uu.se/student peak regions where the interaction density is high. We
present results both on synthetic sample data and data
from the AGO HITS-CLIP study to evaluate our module.
Handledare: Jens Lagergren
Ämnesgranskare: Lars Arvestad
Examinator: Ivan Christoff
IT 13 039
Tryckt av: Reprocentralen ITC

Contents
1 Introduction 3
2 Background 4
2.1 mRNA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.1.1 Transcription . . . . . . . . . . . . . . . . . . . . . . . 4
2.1.2 Translation . . . . . . . . . . . . . . . . . . . . . . . . 5
2.2 miRNA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.3 miRNA-mRNA interaction . . . . . . . . . . . . . . . . . . . 8
2.4 Poisson Distribution . . . . . . . . . . . . . . . . . . . . . . . 8
3 Literature Review 10
4 Methodology 12
4.1 Inputs and their handling . . . . . . . . . . . . . . . . . . . . 12
4.1.1 Selected Genome and Genes . . . . . . . . . . . . . . . 12
4.1.2 Ago HITS-CLIP Data . . . . . . . . . . . . . . . . . . 12
4.2 Synthetic Data Generation . . . . . . . . . . . . . . . . . . . 13
4.2.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . 13
4.2.2 Parameters . . . . . . . . . . . . . . . . . . . . . . . . 14
4.2.3 Generation . . . . . . . . . . . . . . . . . . . . . . . . 18
4.3 Peak (Target Site) Detection . . . . . . . . . . . . . . . . . . 19
4.3.1 Peak Calling . . . . . . . . . . . . . . . . . . . . . . . 19
5 Results 22
5.1 Peak calling on synthetic data . . . . . . . . . . . . . . . . . . 22
5.1.1 P-values . . . . . . . . . . . . . . . . . . . . . . . . . . 22
5.1.2 Peaks called . . . . . . . . . . . . . . . . . . . . . . . . 23
5.2 Peak calling on Ago data . . . . . . . . . . . . . . . . . . . . 26
6 Conclusions 27
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
7 Bibliography 28
2
Chapter 1
Introduction
miRNAs are discovered to regulate gene expression by binding to mRNAs
andcausingthemtodegradeorinhibittheirtranslation. Thisinturna↵ects
how proteins coded by mRNAs that are targeted by miRNAs are generated.
Hence, every life related function they carry out is regulated by miRNAs
(see “Background” for details). This is why we are interested in finding
miRNA target sites on mRNAs.
As Chi et al. [1] provide a platform for investigating miRNA-mRNA in-
teraction, we use the output of their study as input to ours. Aligning the
isolated mRNA tags from the Argonaute-miRNA-mRNA ternary complex
to the genome, we aim to identify regions that are dense in interaction
with miRNAs in this ternary complex. We propose a probabilistic model
of the aligned mRNA tags from [1]. This model is used both for generat-
ing synthetic sample data, and in the target site detection algorithm. The
capability of generating synthetic sample data is important to create a test
bed for the detection algorithm.
The rest of this report is organized as follows: Chapter 2 is meant as a
brief background to the biology and probability theory behind the project,
whilechapter3focusesonasummaryoftherelatedstudies. Methodologyis
presented in chapter 4 and chapter 5 presents the results of our experiments
including their discussions. Finally, chapter 6 concludes the report.
3
Chapter 2
Background
2.1 mRNA
While the essence or meaning of life is an open debate, functions necessary
for life, including catalyzing metabolic reactions and DNA replication, are
carried out by protein molecules. These molecules are encoded by genes in
DNA. Messenger RNAs (mRNA) carry this encoded genetic information for
the amino acid sequence of a protein. Gene expression, namely manufac-
turing a protein, happens in two main phases: transcription which is the
generation of the mRNA; and the translation of the genetic code residing in
the mRNA to a protein [2]. mRNA in prokaryotic and eukaryotic cells have
di↵erent properties and they act slightly di↵erently. We focus on eukary-
otic mRNAs in this study and further discussion considers only eukaryotic
mRNAs.
2.1.1 Transcription
TranscriptionistheprocesswherethemRNAisgeneratedbycomplementing
part of a DNA strand named the template strand including the genetic
information for the protein to be coded. As it can be seen in Fig. 2.1, the
entire process starts with the RNA polymerase enzyme (pol II for mRNA
transcription) binding to the promoter region for the gene in the template
strand of the DNA, which is necessary for the enzyme to be bound to the
DNA. In return, RNA polymerase starts unwinding the DNA and adds the
complementing nucleotide at the 3’ end of the newly generated RNA until
it reaches the termination site. The result is called a pre–mRNA which is
processed further to produce the mature mRNA [2]. This post–processing
is called splicing.
4
Figure2.1: DNAtranscriptiontoRNA.FigurefromSadavaetal.©2008SinauerAssociates[3].
Usedwithpermission.
2.1.2 Translation
Translation is the synthesis process for a protein from the information resid-
ing in the mRNA that is coding this protein (see Fig. 2.2). With the help
of transfer RNAs (tRNA) and the ribosome, the mRNA is read codon by
codon (three base pairs specifying an amino acid) to synthesize the amino
acid chain that constitutes the initial form of a protein. For each codon that
is read, a tRNA with the corresponding anticodon carries the amino acid
coded by the codon to the ribosome and transfers it to the growing amino
5
acid chain [2, 4].
Figure2.2: Summaryofthetranslationprocess. FigurefromMarianaRuizVillarreal/Wikimedia
Commons. Usedwithpermission.
2.2 miRNA
Before we begin introducing miRNA, note that only metazoan miRNAs and
theirfunctionsinmetazoansareconsideredinthisproject. Thus, thereader
should consider our elaboration within metazoans only.
The history of micro RNAs (miRNA) goes back to 1993 [5], where it was
discovered that the LIN-14 protein’s abundance was regulated by a short
RNA product through inhibiting its translation. The discovery was con-
sidered peculiar until in the turn of the millennium, studies reported the
evolutionarily conserved [6] let-7 miRNA to regulate expression of several
genes [7]. Today, a search in PubMed with the keyword ”microRNA” gives
more than 15000 citations, which gives an idea about the amount of interest
in miRNAs in the new century.
6
Figure 2.3: miRNA biogenesis steps. Figure from He and Hannon ©2004 Nature Publishing
Group[8]. Usedwithpermission.
miRNAs are 22-nucleotide residue RNAs. The precursor of the mature
⇠
miRNA is the 70-nucleotide imperfectly base-paired hairpin segment from
⇠
theRNAthatthemiRNAisderivedfrom[9]. Furtherbiogenesisstepsoccur
forthepre-miRNAtobetransformedintothematuremiRNA(seeFig. 2.3).
The mature miRNA, together with Argonaute and several other proteins, is
assembled into a complex named RNA-induced silencing complex (RISC),
which is also referred to as miRNA-protein complex (miRNP). miRNA di-
rects this complex to the binding site on the mRNA in order for the miRNP
to perform its functions on the mRNA.
Rules and regulations for miRNA functions are not crystal clear. This fact
is one of the reasons why there is an increasing amount of diverse research
focused on miRNAs. However, there is some common ground, such as the
fact that the human genome encodes several hundred unique miRNAs and
that these miRNAs interact with thousands of mRNAs [10], which in turn
means that one unique miRNA interacts with more than one mRNA. It
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