Investigating epigenetic patterns induced by diets for health enhancement

1. Investigating epigenetic patterns induced by diets for health enhancement Anna Russo July, 1st Web Valley 2014

2. About Me • BSc in Mathematics at University of Naples “Federico II” • MSc in Mathematics at University of Naples “Federico II” • Third year PhD student in Computational Biology IEO@SEMM in Pier Giuseppe Pelicci group, supervised by Lucilla Luzi Campus IFOM-IEO • Working on: • Whole-exome sequencing data analysis of therapy-related APL patients • Investigating epigenetic patterns induced by different diets and food for health enhancement Pier Giuseppe Pelicci

3. How many times have you heard the expression: “We are what we eat”? What do we mean by that?

4. Two larvae genetically identical... Worker bee I am going to tell you a little story about bees... Queen bee Queen bee

5. Two larvae genetically identical... Worker bee I am going to tell you a little story about bees... Same genotype Two different phenotypes Queen bee Queen bee ...What happened?

6. Honey I am going to tell you a little story about bees... Same genotype Two different phenotypes Queen bee Two larvae genetically identical... Royal Jelly! Worker bee Food acted on the larvae epigenomes!

7. Let's start from the CENTRAL DOGMA of MOLECULAR BIOLOGY DNA Adenine Timine Citosine Transcription Guanine Protein Translation mRNA

8. DNA Adenine Timine Citosine Guanine We can think to the genome as a sequence of letters “ACTGGGGTACAGT...”, as a written text in a book... For example let’s take this sentence... woman without her man is nothing

9. DNA Adenine Timine Citosine Guanine We can think to the genome as a sequence of letters “ACTGGGGTACAGT...”, as a written text in a book... For example let’s take this sentence... woman without her man is nothing What is missing? What do you need to correctly read it?

10. DNA Adenine Timine Citosine Guanine We can think to the genome as a sequence of letters “ACTGGGGTACAGT...”, as a written text in a book... For example let’s take this sentence... woman without her man is nothing What is missing? What do you need to correctly read it? PUNCTUATION! Here how the sentence should be written: woman: without her, man is nothing! (don’t even think to “woman, without her man, is nothing”)

11. DNA Adenine Timine Citosine Guanine We can think to the genome as a sequence of letters “ACTGGGGTACAGT...”, as a written text in a book... For example let’s take this sentence... woman without her man is nothing What is missing? What do you need to correctly read it? PUNCTUATION! Think to epigenetics as the equivalent of punctuation in the DNA transcription-translation mechanism

12. Every cell in our body has the same DNA (and therefore the same genetic instruction sets) and yet maintains different terminal phenotypes. This nongenetic cellular memory, which records developmental and environmental cues, is the basis of epi-(above)–genetics. Stem cell Lymphocyte Neuron Melanocyte … Differentiated cell

13. DNA structure: from the “double helix” to the “pearls chain” histones chromosomes histone tail RNA strand nucleosome DNA + histones = Chromatin nucleus

14. Definition of Epigenome: It's the record of the chemical changes to the DNA and histone proteins of an organism; these changes can be passed down to an organism's offspring. Changes to the epigenome can result in changes to the structure of chromatin and changes to the function of the genome. Histone Modifications DNA methylation

15. Epigenetics is the study of heritable changes in gene expression and function that cannot be explained by changes in DNA sequence Richards 2006; Bird 2007 Environmental and intrinsic factors • Epigenetic Changes • Histone modification • DNA methylation • Influence on: • Gene expression • Phenotype Modification of chromatin structure Regulation of transcription, replication and genome stability

16. Cancer Diet Diet represents one of the main lifestyle factors that can influence the risk of cancer • High Fat Diet • cardiovascular risk • overweight - obesity • metabolic syndrome • tumours • Calorie Restriction • reduce tumour development • increase longevity Chlebowsky et al, 1994; Berrino et al 2006; Pasanisi et al 2006;Shen et al 2010; Breccia et al 2012; Hursting et al 2010; Fontana et al, 2012

17. Epigenetics Diet Unmethylation of the agouti gene results in a yellow coat and obese mouse, prone to diabetes and cancer. Otherwise, the coat color is brown and the mouse has a low disease risk. Feeding pregnant yellow mice with a methyl-rich diet, most of her pups were brown and stayed healthy for life. Food can affect the activity of several chromatin-modifying enzymes Bee larvae producing “queen” phenotype are genetically identical to the ones producing “workers”. The difference is in their diet: the royal jelly silencing Dnmt3, a gene involved in DNA methylation, activates other genes needed to develop functional ovaries, egg laying abdomen and the necessary behavior to act as queen Kurcharski et al, Science 2008 Woloff et al, FASEB journal 1998 Individuals who were prenatally exposed to famine during the Dutch Hunger Winter in 1944–45 had, 6 decades later, less DNA methylation of the imprinted IGF2 gene compared with their unexposed, same-sex siblings. Heijmans et al, PNAS 2008

18. Epigenetics Cancer Epigenetic alterations are ubiquitous, an alternative to genetic changes in gene disruption and sufficient to initiate tumourigenesis Genetics • Activation of Oncogenes/ Deactivation of tumor suppressors • Histone modifications • Global alterations and disruption of epigenetic marks in progenitors cells is a key determinant for both cancer risk, tumor progression and heterogeneity • Increased genomic instability when HMs involved in chromosome structure are altered • Increased mutation rate in regions of heterochromatin because DNA repair mechanism differs (slower and less efficient) in these regions Epigenetics Hansen et al, 2011; Jin et al, 2011; Feinberg et al, 2006; Jones et al 2007,

19. Epigenetics Cancer Diet represents one of the main lifestyle factors that can influence the risk of cancer Diet MECHANISMS? Alterations of both DNA methylation and histones are sufficient to initiate tumourigenesis Food can affect the activity of several chromatin-modifying enzymes

20. Main Questions Do epigenetic changes induced by different diet treatments leave a specific signature? Is it possible to identify diet-specific epigenetic profiles and a set of markers potentially related to cancer? Is it possible to verify if, and for how long, diet-induced epigenetic traits are maintained even in absence of a sustained challenge?

21. Experimental Design Different diets (SD,CR,HF) Bioinformatics Analysis PATChIP seq Liver included in paraffin RNAseq DNA methylation Different durations

22. Mice colonies Different diets (SD,CR,HF) Bioinformatics Analysis PATChIP seq Liver included in paraffin RNAseq DNA methylation Different durations Strain: C57 black 6LACz female ~10 animals for each condition

23. Organs collected Different diets (SD,CR,HF) Bioinformatics Analysis PATChIP seq Liver included in paraffin RNAseq DNA methylation Different durations • But also: • Brain • Lungs • Kidneys • Intestine • Spleen • Abdominal Fat • Heart

24. NGS techniques information Different diets (SD,CR,HF) Bioinformatics Analysis PATChIP seq Liver included in paraffin RNAseq DNA methylation Different durations Protocols Sequencing Information • PATChIP protocol adapted for Liver from Fanelli et al, Nature Protocols 2011 (anti-H3K4me3, anti-H3K27me3) • DNA methylation and RNA extraction from FFPE sections (still on going) Illumina HiSeq2000 ~30 million reads depth

25. Peak calling and peaks annotation Sequencing with Illumina HiSeq2000 PATChIPseq bioinformatics pipeline Visualization of samples and peaks tracks on Genome Browser Different diets (SD,CR,HF) Bioinformatics Analysis Quality filtering with FastQC PATChIP seq Liver included in paraffin RNAseq Alignment with BWA DNA methylation Different durations Peaks basic statistics Pathway analysis Methods for chromatin states characterization Removal of duplicates with SAMtools

26. Pre-processing, peak calling results and enriched pathways Genome Browser view

27. Pre-processing, peak calling results and enriched pathways Genome Browser view

28. Pre-processing, peak calling results and enriched pathways Genome Browser view

29. Pre-processing, peak calling results and enriched pathways Total non redundant peaks for diet group Diet specific peaks Diet specific peaks on genes’ TSSs Unique genes enriched 5,921 1,784 2,272 17,355 19,823 9,765 5,806 8,218 26,588 22,871 6,763 10,065

30. Pre-processing, peak calling results and enriched pathways DAVID annotation tool Proliferation, inflammation, DNA damage, dysregulation of mTOR pathway mRNA transcriptional and post transcriptional regulation

31. Differential Binding analysis - DiffBind OUTPUT Statistical testing is used to decide whether, for a given region, an observed difference in read counts is significant, that is, whether it is greater than what would be expected just due to natural random variation. If reads were independently sampled from a population with given, fixed fractions of genes, the read counts would follow a multinomial distribution, which can be approximated by the Poisson distribution. Since Poisson distribution is too restrictive (it predicts smaller variations than what is seen in the data), the negative binomial distribution. Anders and Huber, Genome Biology 2010 11:R106

32. SD22 SD22 Differential Binding analysis - DiffBind SD73 SD73 OUTPUT SD76 SD76 CR81 CR81 CR79 CR79 HF65 HF65 HF68 HF68 Group DiffBind is able to recognize and cluster SD vs “notSD” group and to divide also CR from HF samples

33. SD22 SD22 Differential Binding analysis - DiffBind SD73 SD73 OUTPUT SD76 SD76 CR81 CR81 CR79 CR79 HF65 HF65 HF68 HF68 Group DiffBind is able to recognize and cluster SD vs “notSD” group and to divide also CR from HF samples

34. Acknowledgments Cesare Furlanello and all the webvalley staff :) Marco Giorgio Costanza Savino Valeriano Gentile Ivan Dellino Luca Mazzarella PGP group Margherita Bodini Luciano Giacò Francesco Santaniello Giorgio Melloni Laura Riva Pier Giuseppe Pelicci Lucilla Luzi Lucilla Titta Krizia Ferrarini Francesca Ghelfi Salvatore Minucci Marco Ballarini Mirko Fanelli Sequencing unit@IEO Salvatore Bianchi Luca Rotta Thank you all for the attention!