Article Review. DNA-methylation effect on co-transcriptional splicing is dependent on GC-architecture of the exon-intron structure

Size: px
Start display at page:

Download "Article Review. DNA-methylation effect on co-transcriptional splicing is dependent on GC-architecture of the exon-intron structure"

Transcription

1 Article Review DNA-methylation effect on co-transcriptional splicing is dependent on GC-architecture of the exon-intron structure 15 March 2013 Genome Research 1

2 Article Genome Research, 15 March 2013, pre-print Publication in 6 months Sahar Gelfman, Noa Cohen, Ahuvi Yearim and Gil Ast Department of Human Molecular Genetics & Biochemistry, Sackler Faculty of Medicine, Tel-Aviv University, Israel 2

3 Field of interest Methylation influence on exons recognition and splicing mechanism. 3

4 Quality Pluses: Field overview Lots of references to related works, data sets Minuses: Not well-written Results aren t clear Only average effect was considered Observes correlation but doesn t explain it 4

5 Already known Splicing is co-trascriptional introns removed while transcript is attached to the DNA by RNA pol II GC content Increased in exons mcg/cg level in exons higher than in introns (Schwartz 2009) The level of mcg/cg decreases with increasing GC levels (..) DNA-methylation Affects transcription Strong exon-boundaries marker (Lauren 2010) Possible splicing regulator (Lauren 2010) Depletion of mc in Hox genes --> removing pol II stalling and facilitating transcriptional elongation and efficient splicing (Tao et al. 2010) 5

6 Background Article: Lister et al. (2009) revealed that there is a higher level of CpG-methylation on exons than on flanking introns. However, this difference was dissolved when values were divided by cytosine composition, since exons have a higher GC content, on average, than their flanking introns (Schwartz et al. 2009) Mean mc/c Profiles Over Genomic Regions. Gene body regions were divided in 20 bins from 5' to 3' end, and the mean mc/c level within each bin for each methylation type was determined (mcg/cg black, mchg/chg red, CHH/CHH blue). (Lister et al. (2009)) 6

7 Already known Nucleosome occupancy Increased along exons (Schwartz et al. 2009) Strongly biased towards high GC content (..) Positioning of nucleosomes Partially determined by the DNA sequence and GC content (..) Chromatin remodelers changes positioning (..) DNA-methylation - chromatin remodeler: rigid nucleosomal conformation binding of methyl-binding proteins (MBPs) Nucleosome - roadblock for polii (polii pauses, unwind DNA, release nucleosome, transcription elongation) (..) Transcriptional pausing may allow co-transcriptional recognition of splicing signals in the pre-mrna (de la Mata et al. 2003). 2 models: Intron recognition, Exon recognition (Amit et al. 2012) 7

8 Hypothesis Change in nucleosome occupancy that accompanies DNA methylation might have an indirect influence on pol II elongation rate and co-transcriptional splicing. RNA PolII pauses at splice sites and let other factors (probably methylation binding proteins) to recognize splice site and take decision to do alternative splicing or not. 8

9 Main Question 1. Could the roles of epigenetic modifications in splicing be a side effect of the GC content of the exons? 2. How could one isolate the measured levels of DNA-methylation and nucleosome occupancy on exons, and conclude a biological role unbiased by GC-content? 9

10 Exons groups Exons by GC content architecture 1. Differential GC - significantly higher GC in exons than flanking introns (p-value < 0.05) 2. Leveled GC - same GC level Exons by Splicing behaviour Alternative - optional included in gene mrnas Constitutive - always in included in gene mrnas 10

11 Agenda Investigations Role of mcg as exons bounds marker Role of mcg in exons recognition and inclusion in mrna Influence of CG dinucleotide on chromatine organization (nucleosome positioning) Role of GC content in exons recognition and chromatin organization Article results Article Bottle necks 11

12 mcg As Exons Marker Differential exons exon based splicing recognition 15,874 exons (RefSeq,? by Amit 2012) Leveled exons intron based splicing recognition 16,269 exons (RefSeq,? by Amit 2012) H1 cells, Salk methylome data (Lister 2009) GC content ATTGGGGCAC - 60% GC content, 0% CG ACGCCAATCG - 60% GC content, 40% CG mcg/cg avg. methylation level per base for each group = (sum of methylation level at each pos) / (exons number with CG in this position) [discussion:?] 12

13 mcg As Exons Marker mcg/cg significantly high in exons vs introns, both groups (p-value < 2.2 x ) intron vs. exons mcg/cg methylation level increase: +6% - differential exons +30% - leveled exons!!!! 13

14 mcg As Exons Marker Basic DNA methylation level by base calls ([?:mc/c]) - strong exons signal CG abundance - strong exons signal in agreement with already know CG di-nucleotide abundance works (Karlin 1995, Gentles 2001) 14

15 mcg As Exons Marker RRBS (reduced representation bisulfite sequencing) - most loci and CpG-rich promoters regions; approx. 5% CpG Mouse - RRBS data exons - nearly same results, noise!!! 15

16 mcg As Exons Marker Different tissues: show nearly same pattern 16

17 mcg As Exons Marker Nucleosome occupancy on exons vs flanking introns (Amit et al. 2012): differential exons : 50% increase leveled exons: 10% increase Although nucleosomes occupancy differs both have strong methylation signal on exons. Group weakly marked by nucleosomes is more significantly marked by methylated CpG 17

18 mc For Exon Recognition mcg/cg level in alternatively and constitutively spliced exons examined to evaluate DNA methylation role in recognition Exons splicing types (alt/const) obtained from RNA-Seq (H1 cellline) SpliceTrap tool - For every exon it quantifies the extent to which it is included, skipped or subjected to size variations due to alternative 3 / 5 splice sites or Intron Retention. In addition, SpliceTrap can quantify alternative splicing within a single cellular condition, with no need of a background set of reads. SpliceTrap approaches the expression-level estimation of each exon as an independent Bayesian inference problem exons with canonical splicing differential exons : 7413 (5734 const, 1679 alternative) leveled exons: 6037 (4936 const, 1101 alternative) 18

19 mc For Exon Recognition exon-intron CG structure as expected in constitutive/alternative exons groups 19

20 mc For Exon Recognition mcg/cg general signal pattern same for differential & leveled GC constitutive exons (multiple t-test, p-value < 2.2x10-16 ) mcg/cg lower in alternative vs. constitutive exons (multiple t-test, p-value < 2.2x10-16 ) 20

21 mc For Exon Recognition Nucleosome occupancy signal Differential GC exons - strong Leveled GC exons - weak 21

22 CG & Chromatine Structure High mcg/cg level was observed near 3, 5 splice sites Does presence of CG dinucleotide in splice signal consensus lead to high mcg/cg? Control dataset pseudo exons (Ke et al. 2011): Pseudo exons - intronic sequences having lengths between 50 and 250 nt and splice site motif score close to splice sites scores In addition, pseudo exons had to be at least 100 nt away from the closest real exon Pseudo exons not biased to any GC differential in exons vs introns 22

23 CG & Chromatine Structure Pseudo exons not biased to any GC differential in exons vs introns 23

24 CpG & Chromatine CG abundance higher in lev., diff. but same in pseudo exons CG high increased (mc in 70% of cases) -> 3 : -5; 5 : -2, +4 3 peaks positions may have a regulatory role. 24

25 CpG & Chromatine Peaks role as chromatin remodelers? Was shown that certain DNA sequences with high affinity binding to the histone can direct nucleosome positioning (Lowary and Widom 1998) DNA methylation may have an intrinsic effect on nucleosome positioning on the DNA (Chodavarapu et al. 2010; Cedar and Bergman 2012) No method found for single by methylation & chromatin organization quantification. CD4+ T cells nucleosomes data (Schones et al. 2008).[discussion:] running average, on 20 nt window 25

26 CpG & Chromatine Methylated CG: ES cells % CG methylated (Lister 2009) [JetBioLabs: 74-87%] 70-88% CG in differentiated & leveled GC groups methylated (Fig.1) => CG dinucleotide acts as representative of methylated position. [discussion:!!!] 70-88% is mlevel of CG-not same %CG methylated Exons sub groups based on mc peak positions CG composition group: CG at the peak position GC composition group: C G, but not GC at the peak position not-c composition group: other nucleotides ( i.e AA,AT,AC,AG..) AG composition group (not-c sub-group): AG at peak position GC group - control for CG group (same GC content) AG group for 5 : -2 position 26

27 CpG & Chromatine Leveled exons - increased nucleosome occupancy when Any of the 3 peak positions is a CG in the group Near 3 peak positions for CG compared to others (multiple t-tests, p-value < ) other positions - trend of increased nucleosome occupancy when a CG is present but the effect is smaller that at the peak. 27

28 CpG & Chromatine Differential exons - less nucleosome occupancy Depleted signal when -5 at 3 site is CG comparing with GC (p-value < 0.006) Small increase for -2 (p-value < ) and +4 (p-value < 0.043) at 5 site other positions - increasing occupancy not observed, occupancy is not significantly affected by dinucleotide composition near the splice site. 28

29 CpG & Chromatine Question: Does CG peaks express some special GC-content signal? CG at 3 peak positions doesn t significantly affect GC content of any sub-group Cannot explain strong nucleosome occupancy signal of CG group in leveled exons 29

30 CpG & Chromatine 3 CG peaks detected close to splicing sites CG at peaks are frequently methylated => Probably directs nucleosomes binding mediated by MBP (methylation binding proteins) Nucleosomal signal Differential CG group - weak CG peaks effect Leveled CG group - strong CG peaks nucleosomal signal => Exons recognition mechanism may depend on the GC environment of exon/gene/location (will be in further works) 30

31 GC Content Role Perhaps difference in epigentic pattern is chromosomes specific due to different GC content? Are Exon-intron patterns (Fig 1,2) dependent on GC content? Isochore maps (Costantini et al. 2006) Isochore maps - regions >= 300 K bases with homogeneous GC content. Core (GC > 46%) and Desert (GC < 46%) parts 31

32 GC Content Role Leveled & Differential group not equally distributed along genome Differential - more in lower GC chromosomes Leveled - in high GC chromosomes 32

33 GC Content Role Exons H1 were divided in core (53 102) and desert (85 979) exons exons RNA-seq data contains only => alt. and const. exons were considered as EST-based (expressed sequence tag) 33

34 GC Content Role Methylation is strong exons marker for both core and desert exons 34

35 GC Content Role Methylated CG level drops (desert & core groups) in alternative exons vs. const. exons Mean mcg level increase for const. vs. alt exons groups core exons +24% mcg level (6 443 of ) desert exons +19% mcg level (9 649 of alt.) 35

36 GC Content Role Nucleosomes occupancy low GC regions: often on exons than introns high GC regions: spread along both exons and introns 36

37 Results Alternative Constitutive Differential Leveled GC content Nucleosomes occupancy n/a n/a high exons marking weak exons marking but CG-related signal presence at 3 positions GC-content dependent Methylation Lower mcpg level on alternative comparing to const. spliced exons Clear marking; Stronger signal on leveled exons; Intronic mc reduction near splice sites. Exons marking GC content independent 37

38 Results GC content bias elimination - Leveled & Diff exons Group weakly marked by nucleosomes is more significantly marked by methylated CpG In a Leveled GC architecture methylated CpGs accompanied higher inclusion of exons, i.e. exons are recognized and aren t removed by splicing. Not the absolute methylation value that distinguishes const. vs alt. exons, but the differential in the ratio of mcpg/cpg between exon and introns, which is also dependent in the general GC environment Supports for the role of DNA methylation as a splicing regulator 38

39 Discussion =?=> CpG methylation can be a part of the code that allows the splicing machinery to locate exons that have no GC differential. Identified a strong decrease in methylated CpGs in alternative exons and their flanking sequences compared with constitutive exons =?=> lower DNA methylation levels of the whole intron-exon-intron strip are associated with suboptimal recognition of alternatively spliced exons Effect on splicing of a strong DNA methylation signal in a leveled GCarchitecture may be indirectly through pol II stalling ( =?=> detected peak in CG abundance) =?=> peaks in CpG methylation at the 5 and 3 splice sites act as the central area binding for the nucleosomal splicing barrier, while the drop in methylated CpGs in intronic flanking regions of leveled GC exons point to the entry/exit regions of the nucleosome. 39

40 Article bottle necks Only CG methylation in ES cells considered, much reasonable to check CG methylation in differentiated cells mcg/cg average methylation level is a vague characteristics. It shows methylation variability at position among different cells in passage. More over Lister (2009) showed that there are large PMM domains in DNA. Seems mcg/cg signal in all cases was induced by higher CG density and signal Nucleosomes binding isn t clear, Chip-Seq based methods provides positions with precision about +/ bp Authors replace mcg with just CG presence in exons. Such trick seemed to be incorrect. Hard to interpret trends in average for a particular exon. 40

41 Tel-Aviv University Differential & Leveled GC content, short/long introns. 2 splicing models (intron/exon recognition). (Amit et al. 2012) Chromatin organization role in splicing (Schwartz et al. 2009) 41

EPIGENETICS DNA and Histone Model

EPIGENETICS DNA and Histone Model EPIGENETICS ABSTRACT A 3-D cut-and-paste model depicting how histone, acetyl and methyl molecules control access to DNA and affect gene expression. LOGISTICS TIME REQUIRED LEARNING OBJECTIVES DNA is coiled

More information

Discovery & Modeling of Genomic Regulatory Networks with Big Data

Discovery & Modeling of Genomic Regulatory Networks with Big Data Discovery & Modeling of Genomic Regulatory Networks with Big Data Hamid Bolouri Division of Human Biology Fred Hutchinson Cancer Research Center labs.fhcrc.org/bolouri I have no financial relationships

More information

Introduction To Epigenetic Regulation: How Can The Epigenomics Core Services Help Your Research? Maria (Ken) Figueroa, M.D. Core Scientific Director

Introduction To Epigenetic Regulation: How Can The Epigenomics Core Services Help Your Research? Maria (Ken) Figueroa, M.D. Core Scientific Director Introduction To Epigenetic Regulation: How Can The Epigenomics Core Services Help Your Research? Maria (Ken) Figueroa, M.D. Core Scientific Director Gene expression depends upon multiple factors Gene Transcription

More information

Introduction to transcriptome analysis using High Throughput Sequencing technologies (HTS)

Introduction to transcriptome analysis using High Throughput Sequencing technologies (HTS) Introduction to transcriptome analysis using High Throughput Sequencing technologies (HTS) A typical RNA Seq experiment Library construction Protocol variations Fragmentation methods RNA: nebulization,

More information

Protein Synthesis How Genes Become Constituent Molecules

Protein Synthesis How Genes Become Constituent Molecules Protein Synthesis Protein Synthesis How Genes Become Constituent Molecules Mendel and The Idea of Gene What is a Chromosome? A chromosome is a molecule of DNA 50% 50% 1. True 2. False True False Protein

More information

GENE REGULATION. Teacher Packet

GENE REGULATION. Teacher Packet AP * BIOLOGY GENE REGULATION Teacher Packet AP* is a trademark of the College Entrance Examination Board. The College Entrance Examination Board was not involved in the production of this material. Pictures

More information

Control of Gene Expression

Control of Gene Expression Control of Gene Expression What is Gene Expression? Gene expression is the process by which informa9on from a gene is used in the synthesis of a func9onal gene product. What is Gene Expression? Figure

More information

Control of Gene Expression

Control of Gene Expression Control of Gene Expression (Learning Objectives) Explain the role of gene expression is differentiation of function of cells which leads to the emergence of different tissues, organs, and organ systems

More information

How Sequencing Experiments Fail

How Sequencing Experiments Fail How Sequencing Experiments Fail v1.0 Simon Andrews simon.andrews@babraham.ac.uk Classes of Failure Technical Tracking Library Contamination Biological Interpretation Something went wrong with a machine

More information

Core Facility Genomics

Core Facility Genomics Core Facility Genomics versatile genome or transcriptome analyses based on quantifiable highthroughput data ascertainment 1 Topics Collaboration with Harald Binder and Clemens Kreutz Project: Microarray

More information

School of Nursing. Presented by Yvette Conley, PhD

School of Nursing. Presented by Yvette Conley, PhD Presented by Yvette Conley, PhD What we will cover during this webcast: Briefly discuss the approaches introduced in the paper: Genome Sequencing Genome Wide Association Studies Epigenomics Gene Expression

More information

DNA Replication & Protein Synthesis. This isn t a baaaaaaaddd chapter!!!

DNA Replication & Protein Synthesis. This isn t a baaaaaaaddd chapter!!! DNA Replication & Protein Synthesis This isn t a baaaaaaaddd chapter!!! The Discovery of DNA s Structure Watson and Crick s discovery of DNA s structure was based on almost fifty years of research by other

More information

Shouguo Gao Ph. D Department of Physics and Comprehensive Diabetes Center

Shouguo Gao Ph. D Department of Physics and Comprehensive Diabetes Center Computational Challenges in Storage, Analysis and Interpretation of Next-Generation Sequencing Data Shouguo Gao Ph. D Department of Physics and Comprehensive Diabetes Center Next Generation Sequencing

More information

Standards, Guidelines and Best Practices for RNA-Seq V1.0 (June 2011) The ENCODE Consortium

Standards, Guidelines and Best Practices for RNA-Seq V1.0 (June 2011) The ENCODE Consortium Standards, Guidelines and Best Practices for RNA-Seq V1.0 (June 2011) The ENCODE Consortium I. Introduction: Sequence based assays of transcriptomes (RNA-seq) are in wide use because of their favorable

More information

Biological Sciences Initiative. Human Genome

Biological Sciences Initiative. Human Genome Biological Sciences Initiative HHMI Human Genome Introduction In 2000, researchers from around the world published a draft sequence of the entire genome. 20 labs from 6 countries worked on the sequence.

More information

Module 3 Questions. 7. Chemotaxis is an example of signal transduction. Explain, with the use of diagrams.

Module 3 Questions. 7. Chemotaxis is an example of signal transduction. Explain, with the use of diagrams. Module 3 Questions Section 1. Essay and Short Answers. Use diagrams wherever possible 1. With the use of a diagram, provide an overview of the general regulation strategies available to a bacterial cell.

More information

The Nucleus: DNA, Chromatin And Chromosomes

The Nucleus: DNA, Chromatin And Chromosomes The Nucleus: DNA, Chromatin And Chromosomes Professor Alfred Cuschieri Department of Anatomy, University of Malta. Objectives By the end of this unit the student should be able to: 1. List the major structural

More information

Frequently Asked Questions Next Generation Sequencing

Frequently Asked Questions Next Generation Sequencing Frequently Asked Questions Next Generation Sequencing Import These Frequently Asked Questions for Next Generation Sequencing are some of the more common questions our customers ask. Questions are divided

More information

AP BIOLOGY 2009 SCORING GUIDELINES

AP BIOLOGY 2009 SCORING GUIDELINES AP BIOLOGY 2009 SCORING GUIDELINES Question 4 The flow of genetic information from DNA to protein in eukaryotic cells is called the central dogma of biology. (a) Explain the role of each of the following

More information

Lecture Series 7. From DNA to Protein. Genotype to Phenotype. Reading Assignments. A. Genes and the Synthesis of Polypeptides

Lecture Series 7. From DNA to Protein. Genotype to Phenotype. Reading Assignments. A. Genes and the Synthesis of Polypeptides Lecture Series 7 From DNA to Protein: Genotype to Phenotype Reading Assignments Read Chapter 7 From DNA to Protein A. Genes and the Synthesis of Polypeptides Genes are made up of DNA and are expressed

More information

Genetic information (DNA) determines structure of proteins DNA RNA proteins cell structure 3.11 3.15 enzymes control cell chemistry ( metabolism )

Genetic information (DNA) determines structure of proteins DNA RNA proteins cell structure 3.11 3.15 enzymes control cell chemistry ( metabolism ) Biology 1406 Exam 3 Notes Structure of DNA Ch. 10 Genetic information (DNA) determines structure of proteins DNA RNA proteins cell structure 3.11 3.15 enzymes control cell chemistry ( metabolism ) Proteins

More information

A Brief Introduction on DNase-Seq Data Aanalysis

A Brief Introduction on DNase-Seq Data Aanalysis A Brief Introduction on DNase-Seq Data Aanalysis Hashem Koohy, Thomas Down, Mikhail Spivakov and Tim Hubbard Spivakov s and Fraser s Lab September 13, 2014 1 Introduction DNaseI is an enzyme which cuts

More information

Expression Quantification (I)

Expression Quantification (I) Expression Quantification (I) Mario Fasold, LIFE, IZBI Sequencing Technology One Illumina HiSeq 2000 run produces 2 times (paired-end) ca. 1,2 Billion reads ca. 120 GB FASTQ file RNA-seq protocol Task

More information

Analysis and Integration of Big Data from Next-Generation Genomics, Epigenomics, and Transcriptomics

Analysis and Integration of Big Data from Next-Generation Genomics, Epigenomics, and Transcriptomics Analysis and Integration of Big Data from Next-Generation Genomics, Epigenomics, and Transcriptomics Christopher Benner, PhD Director, Integrative Genomics and Bioinformatics Core (IGC) idash Webinar,

More information

Comparing Methods for Identifying Transcription Factor Target Genes

Comparing Methods for Identifying Transcription Factor Target Genes Comparing Methods for Identifying Transcription Factor Target Genes Alena van Bömmel (R 3.3.73) Matthew Huska (R 3.3.18) Max Planck Institute for Molecular Genetics Folie 1 Transcriptional Regulation TF

More information

Computational localization of promoters and transcription start sites in mammalian genomes

Computational localization of promoters and transcription start sites in mammalian genomes Computational localization of promoters and transcription start sites in mammalian genomes Thomas Down This dissertation is submitted for the degree of Doctor of Philosophy Wellcome Trust Sanger Institute

More information

Human Genome Organization: An Update. Genome Organization: An Update

Human Genome Organization: An Update. Genome Organization: An Update Human Genome Organization: An Update Genome Organization: An Update Highlights of Human Genome Project Timetable Proposed in 1990 as 3 billion dollar joint venture between DOE and NIH with 15 year completion

More information

Bioinformatics Resources at a Glance

Bioinformatics Resources at a Glance Bioinformatics Resources at a Glance A Note about FASTA Format There are MANY free bioinformatics tools available online. Bioinformaticists have developed a standard format for nucleotide and protein sequences

More information

To be able to describe polypeptide synthesis including transcription and splicing

To be able to describe polypeptide synthesis including transcription and splicing Thursday 8th March COPY LO: To be able to describe polypeptide synthesis including transcription and splicing Starter Explain the difference between transcription and translation BATS Describe and explain

More information

Overview of Eukaryotic Gene Prediction

Overview of Eukaryotic Gene Prediction Overview of Eukaryotic Gene Prediction CBB 231 / COMPSCI 261 W.H. Majoros What is DNA? Nucleus Chromosome Telomere Centromere Cell Telomere base pairs histones DNA (double helix) DNA is a Double Helix

More information

Transcription in prokaryotes. Elongation and termination

Transcription in prokaryotes. Elongation and termination Transcription in prokaryotes Elongation and termination After initiation the σ factor leaves the scene. Core polymerase is conducting the elongation of the chain. The core polymerase contains main nucleotide

More information

Appendix 2 Molecular Biology Core Curriculum. Websites and Other Resources

Appendix 2 Molecular Biology Core Curriculum. Websites and Other Resources Appendix 2 Molecular Biology Core Curriculum Websites and Other Resources Chapter 1 - The Molecular Basis of Cancer 1. Inside Cancer http://www.insidecancer.org/ From the Dolan DNA Learning Center Cold

More information

How To Understand How Gene Expression Is Regulated

How To Understand How Gene Expression Is Regulated What makes cells different from each other? How do cells respond to information from environment? Regulation of: - Transcription - prokaryotes - eukaryotes - mrna splicing - mrna localisation and translation

More information

Algorithms in Computational Biology (236522) spring 2007 Lecture #1

Algorithms in Computational Biology (236522) spring 2007 Lecture #1 Algorithms in Computational Biology (236522) spring 2007 Lecture #1 Lecturer: Shlomo Moran, Taub 639, tel 4363 Office hours: Tuesday 11:00-12:00/by appointment TA: Ilan Gronau, Taub 700, tel 4894 Office

More information

Just the Facts: A Basic Introduction to the Science Underlying NCBI Resources

Just the Facts: A Basic Introduction to the Science Underlying NCBI Resources 1 of 8 11/7/2004 11:00 AM National Center for Biotechnology Information About NCBI NCBI at a Glance A Science Primer Human Genome Resources Model Organisms Guide Outreach and Education Databases and Tools

More information

MORPHEUS. http://biodev.cea.fr/morpheus/ Prediction of Transcription Factors Binding Sites based on Position Weight Matrix.

MORPHEUS. http://biodev.cea.fr/morpheus/ Prediction of Transcription Factors Binding Sites based on Position Weight Matrix. MORPHEUS http://biodev.cea.fr/morpheus/ Prediction of Transcription Factors Binding Sites based on Position Weight Matrix. Reference: MORPHEUS, a Webtool for Transcripton Factor Binding Analysis Using

More information

How many of you have checked out the web site on protein-dna interactions?

How many of you have checked out the web site on protein-dna interactions? How many of you have checked out the web site on protein-dna interactions? Example of an approximately 40,000 probe spotted oligo microarray with enlarged inset to show detail. Find and be ready to discuss

More information

PrimePCR Assay Validation Report

PrimePCR Assay Validation Report Gene Information Gene Name Gene Symbol Organism Gene Summary Gene Aliases RefSeq Accession No. UniGene ID Ensembl Gene ID papillary renal cell carcinoma (translocation-associated) PRCC Human This gene

More information

The world of non-coding RNA. Espen Enerly

The world of non-coding RNA. Espen Enerly The world of non-coding RNA Espen Enerly ncrna in general Different groups Small RNAs Outline mirnas and sirnas Speculations Common for all ncrna Per def.: never translated Not spurious transcripts Always/often

More information

2. The number of different kinds of nucleotides present in any DNA molecule is A) four B) six C) two D) three

2. The number of different kinds of nucleotides present in any DNA molecule is A) four B) six C) two D) three Chem 121 Chapter 22. Nucleic Acids 1. Any given nucleotide in a nucleic acid contains A) two bases and a sugar. B) one sugar, two bases and one phosphate. C) two sugars and one phosphate. D) one sugar,

More information

INTERNATIONAL CONFERENCE ON HARMONISATION OF TECHNICAL REQUIREMENTS FOR REGISTRATION OF PHARMACEUTICALS FOR HUMAN USE Q5B

INTERNATIONAL CONFERENCE ON HARMONISATION OF TECHNICAL REQUIREMENTS FOR REGISTRATION OF PHARMACEUTICALS FOR HUMAN USE Q5B INTERNATIONAL CONFERENCE ON HARMONISATION OF TECHNICAL REQUIREMENTS FOR REGISTRATION OF PHARMACEUTICALS FOR HUMAN USE ICH HARMONISED TRIPARTITE GUIDELINE QUALITY OF BIOTECHNOLOGICAL PRODUCTS: ANALYSIS

More information

Challenges associated with analysis and storage of NGS data

Challenges associated with analysis and storage of NGS data Challenges associated with analysis and storage of NGS data Gabriella Rustici Research and training coordinator Functional Genomics Group gabry@ebi.ac.uk Next-generation sequencing Next-generation sequencing

More information

Discovery and Quantification of RNA with RNASeq Roderic Guigó Serra Centre de Regulació Genòmica (CRG) roderic.guigo@crg.cat

Discovery and Quantification of RNA with RNASeq Roderic Guigó Serra Centre de Regulació Genòmica (CRG) roderic.guigo@crg.cat Bioinformatique et Séquençage Haut Débit, Discovery and Quantification of RNA with RNASeq Roderic Guigó Serra Centre de Regulació Genòmica (CRG) roderic.guigo@crg.cat 1 RNA Transcription to RNA and subsequent

More information

Lecture 1 MODULE 3 GENE EXPRESSION AND REGULATION OF GENE EXPRESSION. Professor Bharat Patel Office: Science 2, 2.36 Email: b.patel@griffith.edu.

Lecture 1 MODULE 3 GENE EXPRESSION AND REGULATION OF GENE EXPRESSION. Professor Bharat Patel Office: Science 2, 2.36 Email: b.patel@griffith.edu. Lecture 1 MODULE 3 GENE EXPRESSION AND REGULATION OF GENE EXPRESSION Professor Bharat Patel Office: Science 2, 2.36 Email: b.patel@griffith.edu.au What is Gene Expression & Gene Regulation? 1. Gene Expression

More information

Systematic discovery of regulatory motifs in human promoters and 30 UTRs by comparison of several mammals

Systematic discovery of regulatory motifs in human promoters and 30 UTRs by comparison of several mammals Systematic discovery of regulatory motifs in human promoters and 30 UTRs by comparison of several mammals Xiaohui Xie 1, Jun Lu 1, E. J. Kulbokas 1, Todd R. Golub 1, Vamsi Mootha 1, Kerstin Lindblad-Toh

More information

Replication Study Guide

Replication Study Guide Replication Study Guide This study guide is a written version of the material you have seen presented in the replication unit. Self-reproduction is a function of life that human-engineered systems have

More information

Systems Biology through Data Analysis and Simulation

Systems Biology through Data Analysis and Simulation Biomolecular Networks Initiative Systems Biology through Data Analysis and Simulation William Cannon Computational Biosciences 5/30/03 Cellular Dynamics Microbial Cell Dynamics Data Mining Nitrate NARX

More information

Introduction to Genome Annotation

Introduction to Genome Annotation Introduction to Genome Annotation AGCGTGGTAGCGCGAGTTTGCGAGCTAGCTAGGCTCCGGATGCGA CCAGCTTTGATAGATGAATATAGTGTGCGCGACTAGCTGTGTGTT GAATATATAGTGTGTCTCTCGATATGTAGTCTGGATCTAGTGTTG GTGTAGATGGAGATCGCGTAGCGTGGTAGCGCGAGTTTGCGAGCT

More information

Interaktionen von Nukleinsäuren und Proteinen

Interaktionen von Nukleinsäuren und Proteinen Sonja Prohaska Computational EvoDevo Universitaet Leipzig June 9, 2015 DNA is never naked in a cell DNA is usually in association with proteins. In all domains of life there are small, basic chromosomal

More information

Next Generation Sequencing: Technology, Mapping, and Analysis

Next Generation Sequencing: Technology, Mapping, and Analysis Next Generation Sequencing: Technology, Mapping, and Analysis Gary Benson Computer Science, Biology, Bioinformatics Boston University gbenson@bu.edu http://tandem.bu.edu/ The Human Genome Project took

More information

Lezioni Dipartimento di Oncologia Farmacologia Molecolare. RNA interference. Giovanna Damia 29 maggio 2006

Lezioni Dipartimento di Oncologia Farmacologia Molecolare. RNA interference. Giovanna Damia 29 maggio 2006 Lezioni Dipartimento di Oncologia Farmacologia Molecolare RNA interference Giovanna Damia 29 maggio 2006 RNA INTERFERENCE Sequence-specific gene suppression by dsrnas Gene silencing by dsrna: C. elegans

More information

Genomes and SNPs in Malaria and Sickle Cell Anemia

Genomes and SNPs in Malaria and Sickle Cell Anemia Genomes and SNPs in Malaria and Sickle Cell Anemia Introduction to Genome Browsing with Ensembl Ensembl The vast amount of information in biological databases today demands a way of organising and accessing

More information

Name Class Date. Figure 13 1. 2. Which nucleotide in Figure 13 1 indicates the nucleic acid above is RNA? a. uracil c. cytosine b. guanine d.

Name Class Date. Figure 13 1. 2. Which nucleotide in Figure 13 1 indicates the nucleic acid above is RNA? a. uracil c. cytosine b. guanine d. 13 Multiple Choice RNA and Protein Synthesis Chapter Test A Write the letter that best answers the question or completes the statement on the line provided. 1. Which of the following are found in both

More information

Chapter 5: Organization and Expression of Immunoglobulin Genes

Chapter 5: Organization and Expression of Immunoglobulin Genes Chapter 5: Organization and Expression of Immunoglobulin Genes I. Genetic Model Compatible with Ig Structure A. Two models for Ab structure diversity 1. Germ-line theory: maintained that the genome contributed

More information

Transcription and Translation of DNA

Transcription and Translation of DNA Transcription and Translation of DNA Genotype our genetic constitution ( makeup) is determined (controlled) by the sequence of bases in its genes Phenotype determined by the proteins synthesised when genes

More information

Linking the Epigenome to the Genome: Correlation of Different Features to DNA Methylation of CpG Islands

Linking the Epigenome to the Genome: Correlation of Different Features to DNA Methylation of CpG Islands Linking the Epigenome to the Genome: Correlation of Different Features to DNA Methylation of CpG Islands Clemens Wrzodek*, Finja Büchel, Georg Hinselmann, Johannes Eichner, Florian Mittag, Andreas Zell

More information

FlipFlop: Fast Lasso-based Isoform Prediction as a Flow Problem

FlipFlop: Fast Lasso-based Isoform Prediction as a Flow Problem FlipFlop: Fast Lasso-based Isoform Prediction as a Flow Problem Elsa Bernard Laurent Jacob Julien Mairal Jean-Philippe Vert September 24, 2013 Abstract FlipFlop implements a fast method for de novo transcript

More information

RNAseq / ChipSeq / Methylseq and personalized genomics

RNAseq / ChipSeq / Methylseq and personalized genomics RNAseq / ChipSeq / Methylseq and personalized genomics 7711 Lecture Subhajyo) De, PhD Division of Biomedical Informa)cs and Personalized Biomedicine, Department of Medicine University of Colorado School

More information

13.4 Gene Regulation and Expression

13.4 Gene Regulation and Expression 13.4 Gene Regulation and Expression Lesson Objectives Describe gene regulation in prokaryotes. Explain how most eukaryotic genes are regulated. Relate gene regulation to development in multicellular organisms.

More information

Next Generation Sequencing: Adjusting to Big Data. Daniel Nicorici, Dr.Tech. Statistikot Suomen Lääketeollisuudessa 29.10.2013

Next Generation Sequencing: Adjusting to Big Data. Daniel Nicorici, Dr.Tech. Statistikot Suomen Lääketeollisuudessa 29.10.2013 Next Generation Sequencing: Adjusting to Big Data Daniel Nicorici, Dr.Tech. Statistikot Suomen Lääketeollisuudessa 29.10.2013 Outline Human Genome Project Next-Generation Sequencing Personalized Medicine

More information

Antibody Structure, and the Generation of B-cell Diversity CHAPTER 4 04/05/15. Different Immunoglobulins

Antibody Structure, and the Generation of B-cell Diversity CHAPTER 4 04/05/15. Different Immunoglobulins Antibody Structure, and the Generation of B-cell Diversity B cells recognize their antigen without needing an antigen presenting cell CHAPTER 4 Structure of Immunoglobulin G Different Immunoglobulins Differences

More information

Gene Models & Bed format: What they represent.

Gene Models & Bed format: What they represent. GeneModels&Bedformat:Whattheyrepresent. Gene models are hypotheses about the structure of transcripts produced by a gene. Like all models, they may be correct, partly correct, or entirely wrong. Typically,

More information

RETRIEVING SEQUENCE INFORMATION. Nucleotide sequence databases. Database search. Sequence alignment and comparison

RETRIEVING SEQUENCE INFORMATION. Nucleotide sequence databases. Database search. Sequence alignment and comparison RETRIEVING SEQUENCE INFORMATION Nucleotide sequence databases Database search Sequence alignment and comparison Biological sequence databases Originally just a storage place for sequences. Currently the

More information

DNA and the Cell. Version 2.3. English version. ELLS European Learning Laboratory for the Life Sciences

DNA and the Cell. Version 2.3. English version. ELLS European Learning Laboratory for the Life Sciences DNA and the Cell Anastasios Koutsos Alexandra Manaia Julia Willingale-Theune Version 2.3 English version ELLS European Learning Laboratory for the Life Sciences Anastasios Koutsos, Alexandra Manaia and

More information

Reduced Representation Bisulfite-Seq A Brief Guide to RRBS

Reduced Representation Bisulfite-Seq A Brief Guide to RRBS April 17, 2013 Reduced Representation Bisulfite-Seq A Brief Guide to RRBS What is RRBS? Typically, RRBS samples are generated by digesting genomic DNA with the restriction endonuclease MspI. This is followed

More information

RT 2 Profiler PCR Array: Web-Based Data Analysis Tutorial

RT 2 Profiler PCR Array: Web-Based Data Analysis Tutorial RT 2 Profiler PCR Array: Web-Based Data Analysis Tutorial Samuel J. Rulli, Jr., Ph.D. qpcr-applications Scientist Samuel.Rulli@QIAGEN.com Pathway Focused Research from Sample Prep to Data Analysis! -2-

More information

Control of Gene Expression

Control of Gene Expression Home Gene Regulation Is Necessary? Control of Gene Expression By switching genes off when they are not needed, cells can prevent resources from being wasted. There should be natural selection favoring

More information

Special report. Chronic Lymphocytic Leukemia (CLL) Genomic Biology 3020 April 20, 2006

Special report. Chronic Lymphocytic Leukemia (CLL) Genomic Biology 3020 April 20, 2006 Special report Chronic Lymphocytic Leukemia (CLL) Genomic Biology 3020 April 20, 2006 Gene And Protein The gene that causes the mutation is CCND1 and the protein NP_444284 The mutation deals with the cell

More information

New Technologies for Sensitive, Low-Input RNA-Seq. Clontech Laboratories, Inc.

New Technologies for Sensitive, Low-Input RNA-Seq. Clontech Laboratories, Inc. New Technologies for Sensitive, Low-Input RNA-Seq Clontech Laboratories, Inc. Outline Introduction Single-Cell-Capable mrna-seq Using SMART Technology SMARTer Ultra Low RNA Kit for the Fluidigm C 1 System

More information

Genome-wide measurements of protein-dna interaction by chromatin immunoprecipitation

Genome-wide measurements of protein-dna interaction by chromatin immunoprecipitation Genome-wide measurements of protein-dna interaction by chromatin immunoprecipitation D. Puthier. laboratoire INSERM, Aix-Marseille Université, TAGC/INSERM U928, Parc Scientifique de Luminy case 928 Outline

More information

Structure and Function of DNA

Structure and Function of DNA Structure and Function of DNA DNA and RNA Structure DNA and RNA are nucleic acids. They consist of chemical units called nucleotides. The nucleotides are joined by a sugar-phosphate backbone. The four

More information

Genetics Lecture Notes 7.03 2005. Lectures 1 2

Genetics Lecture Notes 7.03 2005. Lectures 1 2 Genetics Lecture Notes 7.03 2005 Lectures 1 2 Lecture 1 We will begin this course with the question: What is a gene? This question will take us four lectures to answer because there are actually several

More information

PREDA S4-classes. Francesco Ferrari October 13, 2015

PREDA S4-classes. Francesco Ferrari October 13, 2015 PREDA S4-classes Francesco Ferrari October 13, 2015 Abstract This document provides a description of custom S4 classes used to manage data structures for PREDA: an R package for Position RElated Data Analysis.

More information

Lectures 1 and 8 15. February 7, 2013. Genomics 2012: Repetitorium. Peter N Robinson. VL1: Next- Generation Sequencing. VL8 9: Variant Calling

Lectures 1 and 8 15. February 7, 2013. Genomics 2012: Repetitorium. Peter N Robinson. VL1: Next- Generation Sequencing. VL8 9: Variant Calling Lectures 1 and 8 15 February 7, 2013 This is a review of the material from lectures 1 and 8 14. Note that the material from lecture 15 is not relevant for the final exam. Today we will go over the material

More information

CONTRACTING ORGANIZATION: University of Alabama at Birmingham Birmingham, AL 35294

CONTRACTING ORGANIZATION: University of Alabama at Birmingham Birmingham, AL 35294 AD Award Number: W81XWH-08-1-0030 TITLE: Regulation of Prostate Cancer Bone Metastasis by DKK1 PRINCIPAL INVESTIGATOR: Gregory A. Clines, M.D., Ph.D. CONTRACTING ORGANIZATION: University of Alabama at

More information

RNA & Protein Synthesis

RNA & Protein Synthesis RNA & Protein Synthesis Genes send messages to cellular machinery RNA Plays a major role in process Process has three phases (Genetic) Transcription (Genetic) Translation Protein Synthesis RNA Synthesis

More information

Gene Expression Analysis

Gene Expression Analysis Gene Expression Analysis Jie Peng Department of Statistics University of California, Davis May 2012 RNA expression technologies High-throughput technologies to measure the expression levels of thousands

More information

Understanding West Nile Virus Infection

Understanding West Nile Virus Infection Understanding West Nile Virus Infection The QIAGEN Bioinformatics Solution: Biomedical Genomics Workbench (BXWB) + Ingenuity Pathway Analysis (IPA) Functional Genomics & Predictive Medicine, May 21-22,

More information

Central Dogma. Lecture 10. Discussing DNA replication. DNA Replication. DNA mutation and repair. Transcription

Central Dogma. Lecture 10. Discussing DNA replication. DNA Replication. DNA mutation and repair. Transcription Central Dogma transcription translation DNA RNA Protein replication Discussing DNA replication (Nucleus of eukaryote, cytoplasm of prokaryote) Recall Replication is semi-conservative and bidirectional

More information

European Medicines Agency

European Medicines Agency European Medicines Agency July 1996 CPMP/ICH/139/95 ICH Topic Q 5 B Quality of Biotechnological Products: Analysis of the Expression Construct in Cell Lines Used for Production of r-dna Derived Protein

More information

Current Motif Discovery Tools and their Limitations

Current Motif Discovery Tools and their Limitations Current Motif Discovery Tools and their Limitations Philipp Bucher SIB / CIG Workshop 3 October 2006 Trendy Concepts and Hypotheses Transcription regulatory elements act in a context-dependent manner.

More information

Human-Mouse Synteny in Functional Genomics Experiment

Human-Mouse Synteny in Functional Genomics Experiment Human-Mouse Synteny in Functional Genomics Experiment Ksenia Krasheninnikova University of the Russian Academy of Sciences, JetBrains krasheninnikova@gmail.com September 18, 2012 Ksenia Krasheninnikova

More information

PreciseTM Whitepaper

PreciseTM Whitepaper Precise TM Whitepaper Introduction LIMITATIONS OF EXISTING RNA-SEQ METHODS Correctly designed gene expression studies require large numbers of samples, accurate results and low analysis costs. Analysis

More information

1 Mutation and Genetic Change

1 Mutation and Genetic Change CHAPTER 14 1 Mutation and Genetic Change SECTION Genes in Action KEY IDEAS As you read this section, keep these questions in mind: What is the origin of genetic differences among organisms? What kinds

More information

Hierarchical Bayesian Modeling of the HIV Response to Therapy

Hierarchical Bayesian Modeling of the HIV Response to Therapy Hierarchical Bayesian Modeling of the HIV Response to Therapy Shane T. Jensen Department of Statistics, The Wharton School, University of Pennsylvania March 23, 2010 Joint Work with Alex Braunstein and

More information

The Making of the Fittest: Evolving Switches, Evolving Bodies

The Making of the Fittest: Evolving Switches, Evolving Bodies OVERVIEW MODELING THE REGULATORY SWITCHES OF THE PITX1 GENE IN STICKLEBACK FISH This hands-on activity supports the short film, The Making of the Fittest:, and aims to help students understand eukaryotic

More information

Sample Questions for Exam 3

Sample Questions for Exam 3 Sample Questions for Exam 3 1. All of the following occur during prometaphase of mitosis in animal cells except a. the centrioles move toward opposite poles. b. the nucleolus can no longer be seen. c.

More information

Graphical Modeling for Genomic Data

Graphical Modeling for Genomic Data Graphical Modeling for Genomic Data Carel F.W. Peeters cf.peeters@vumc.nl Joint work with: Wessel N. van Wieringen Mark A. van de Wiel Molecular Biostatistics Unit Dept. of Epidemiology & Biostatistics

More information

PrimePCR Assay Validation Report

PrimePCR Assay Validation Report Gene Information Gene Name sorbin and SH3 domain containing 2 Gene Symbol Organism Gene Summary Gene Aliases RefSeq Accession No. UniGene ID Ensembl Gene ID SORBS2 Human Arg and c-abl represent the mammalian

More information

Transcription: RNA Synthesis, Processing & Modification

Transcription: RNA Synthesis, Processing & Modification Transcription: RNA Synthesis, Processing & Modification 1 Central dogma DNA RNA Protein Reverse transcription 2 Transcription The process of making RNA from DNA Produces all type of RNA mrna, trna, rrna,

More information

DNA Insertions and Deletions in the Human Genome. Philipp W. Messer

DNA Insertions and Deletions in the Human Genome. Philipp W. Messer DNA Insertions and Deletions in the Human Genome Philipp W. Messer Genetic Variation CGACAATAGCGCTCTTACTACGTGTATCG : : CGACAATGGCGCT---ACTACGTGCATCG 1. Nucleotide mutations 2. Genomic rearrangements 3.

More information

MeDIP-chip service report

MeDIP-chip service report MeDIP-chip service report Wednesday, 20 August, 2008 Sample source: Cells from University of *** Customer: ****** Organization: University of *** Contents of this service report General information and

More information

BBSRC TECHNOLOGY STRATEGY: TECHNOLOGIES NEEDED BY RESEARCH KNOWLEDGE PROVIDERS

BBSRC TECHNOLOGY STRATEGY: TECHNOLOGIES NEEDED BY RESEARCH KNOWLEDGE PROVIDERS BBSRC TECHNOLOGY STRATEGY: TECHNOLOGIES NEEDED BY RESEARCH KNOWLEDGE PROVIDERS 1. The Technology Strategy sets out six areas where technological developments are required to push the frontiers of knowledge

More information

Translation Study Guide

Translation Study Guide Translation Study Guide This study guide is a written version of the material you have seen presented in the replication unit. In translation, the cell uses the genetic information contained in mrna to

More information

Final Project Report

Final Project Report CPSC545 by Introduction to Data Mining Prof. Martin Schultz & Prof. Mark Gerstein Student Name: Yu Kor Hugo Lam Student ID : 904907866 Due Date : May 7, 2007 Introduction Final Project Report Pseudogenes

More information

Name Date Period. 2. When a molecule of double-stranded DNA undergoes replication, it results in

Name Date Period. 2. When a molecule of double-stranded DNA undergoes replication, it results in DNA, RNA, Protein Synthesis Keystone 1. During the process shown above, the two strands of one DNA molecule are unwound. Then, DNA polymerases add complementary nucleotides to each strand which results

More information

Plant Growth & Development. Growth Stages. Differences in the Developmental Mechanisms of Plants and Animals. Development

Plant Growth & Development. Growth Stages. Differences in the Developmental Mechanisms of Plants and Animals. Development Plant Growth & Development Plant body is unable to move. To survive and grow, plants must be able to alter its growth, development and physiology. Plants are able to produce complex, yet variable forms

More information

Quantitative proteomics background

Quantitative proteomics background Proteomics data analysis seminar Quantitative proteomics and transcriptomics of anaerobic and aerobic yeast cultures reveals post transcriptional regulation of key cellular processes de Groot, M., Daran

More information

Faculty of Medicine. Settore disciplinare: BIO/10. functional domains. Monica Soldi. IFOM-IEO Campus, Milan. Matricola n. R08407

Faculty of Medicine. Settore disciplinare: BIO/10. functional domains. Monica Soldi. IFOM-IEO Campus, Milan. Matricola n. R08407 PhD degree in Molecular Medicine European School of Molecular Medicine (SEMM), University of Milan and University of Naples Federico II Faculty of Medicine Settore disciplinare: BIO/10 Establishment and

More information

Searching Nucleotide Databases

Searching Nucleotide Databases Searching Nucleotide Databases 1 When we search a nucleic acid databases, Mascot always performs a 6 frame translation on the fly. That is, 3 reading frames from the forward strand and 3 reading frames

More information