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Firstly, I would like to thank Professor Eytan Domany, my supervisor, for making it all happen. He is

definitely the one to thank for creating an environment that is both fun and challenging, he has

exposed me to many interesting fields of research and I learned from him much more than he realizes.

Eytan – you’re one of a kind.

Assif Yitzhaky and Hilah Gal were my roomies; Assif taught me everything I know about Matlab and

about working with gene expression and Hilah devotedly took care of my mental health. It was a

pleasure sharing this time with them.

It was a great honor collaborating with Professor Leo Sachs and Dr. Joseph Lotem on the cancer

project, and with Professor David Givol on the mesenchymal stem cell project. They have inspired me

greatly and amazed me with their diligence and vast biological knowledge.

I wish to thank Prof. Dan Gazit and Dr. Hadi Haslan from the Hebrew University for the

collaboration on the mesenchymal stem cell project.

I would also like to thank Eytan’s talented past and present group members for helping me with my

work and for making it a fun thing to do: Noam Shental, Hilah Benjamin, Shiri Margel, Michal

Mashiach, Or Zuk, Roman Brinzanik, Liat Ein-Dor, Garold Fuks, Libi Hertzberg, Itai Kela, Anat

Reiner, Jacob Bock Axelsen, Shlomo Urbach, Mark Koudritsky and Paz Polak. Special thanks to

Michal Sheffer, Tal Shay, Yuval Tabach and Dafna Tsafrir – for sharing their experience with me and

for teaching me so many things.

I also wish to thank Mr. Yossi Drier for the technical support.

Irit Fishel – my dear girlfriend shared the weight of giving birth to this thesis with me and was a

source of endless wise insights and trustworthy statistical support.

Finally – to my beloved family – thank you guys for everything.

THANK YOU ALL AND GOOD LUCK IN ALL YOUR FUTURE ENDEAVORS!

Dvir

4

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Abstract............................................................................................................................ 9 Abstract

General Methods......................................................................................................... 11 General Methods

DNA microarray technology ............................................................................... 11

Dataset compilation and preprocessing ........................................................ 17 General ................................................................................................................... 17 Scaling .................................................................................................................... 19 Removal of all-absent probe-sets ................................................................ 19 Applying Log2 transformation....................................................................... 20 Setting a threshold ............................................................................................ 20 Variability filter ................................................................................................... 21 Centering and Normalization......................................................................... 21 Comments ............................................................................................................. 21

Supervised data analysis methods .................................................................. 22 Fold change .......................................................................................................... 22 T-test and Rank-sum ........................................................................................ 23 ANOVA .................................................................................................................... 23 The multiplicity problem and FDR ............................................................... 24 Gene Ontology (GO) and gene class testing ............................................ 25

Unsupervised data analysis methods ............................................................. 27 Hierarchical clustering ..................................................................................... 27 The SPC clustering algorithm ........................................................................ 28 CTWC....................................................................................................................... 29

Mesenchymal Stem Cell Differentiation ............................................................ 33 Mesenchymal Stem Cell Differentiation

Biological Background.......................................................................................... 33 Biological Background Mesenchymal Stem Cells ................................................................................. 38 Importance of stem cell research ................................................................ 40 Gene expression and stem cell differentiation ....................................... 42

Research Question................................................................................................. 44 Research Question

Materials and Methods ......................................................................................... 45 Embryonic stem cells ........................................................................................ 45 Mesenchymal cells ............................................................................................. 45 Microarrays production .................................................................................... 48

Dataset Structure Scheme .................................................................................. 49 Dataset Structure Scheme

Results........................................................................................................................ 50 Results Global gene expression analysis along the differentiation pathway ................................................................................................................................... 50

6

Counting differentially expressed genes................................................... 56 Identification of genes changed upon induction ................................... 60 Clustering analysis............................................................................................. 76

Summary and Discussion .................................................................................... 81 Discussion Leukemic Over Expression of Tissue Specific Genes .................................... 87 Leukemic Over Expression of Tissue Specific Genes

Biological Background.......................................................................................... 87 Biological Background General Introduction to Cancer .................................................................... 87 General Introduction to Cancer Arrest of Differentiation and Tumorigenesis – AML as an Example 88 Differentiation Therapy.................................................................................... 91 Cancer and Stem Cells...................................................................................... 92 Adult Stem Cell Plasticity and the Prospects of ‘Trans- Differentiation Therapy’ .................................................................................. 95

The Questions Posed............................................................................................. 97 The Questions Posed

Materials and Methods......................................................................................... 98 Materials and Methods Data sets................................................................................................................ 98 Clustering of Highly Variable Genes in Normal Human Tissues ....... 99 Identification of Highly Expressed Genes................................................. 99

Results...................................................................................................................... 101 Results Clustering of Highly Variable Genes in Normal Human Tissues ..... 101 Testing for Distortion due to Normalization .......................................... 104 Identification of Genes that are Over Expressed in Leukemic Cells from Human Patients with Different Subtypes of Lymphoid or Myeloid Leukemia ............................................................................................ 108 Identification of Genes that are over Expressed in SW480 Adenocarcinoma Cell Line ............................................................................. 109

Discussion ................................................................................................................... 111

References ...................................................