Human-Mouse Synteny in Functional Genomics Experiment
|
|
|
- Frank Watkins
- 8 years ago
- Views:
Transcription
1 Human-Mouse Synteny in Functional Genomics Experiment Ksenia Krasheninnikova University of the Russian Academy of Sciences, JetBrains September 18, 2012 Ksenia Krasheninnikova (AU) Human-Mouse Synteny September 18, / 20
2 Objectives 1 Obtain the synteny blocks between the genomes of Homo Sapiens (hg18) and Mus Musculus (mm9) 2 Study genetic properties of the syntenic data (genome coverage, locuses) 3 Study epigenetic properties of the syntenic data (compare the methylation level in synteny blocks) Ksenia Krasheninnikova (AU) Human-Mouse Synteny September 18, / 20
3 Outline Human-Mouse Synteny Approaches to reveal conserved regions Evolutional properties of transcription start sites Enlightment Ksenia Krasheninnikova (AU) Human-Mouse Synteny September 18, / 20
4 Facts about the Human-Mouse Relation Evolutional distance: 75 million years of evolution Human genome size: 3,107,677,273 bp [hg18, UCSC] Mouse genome size: 2,716,965,481 bp [mm9, Reference assembly (C57BL/6J, golden path )] synteny blocks between human and mouse 90.2% of the human genome and 93.3% of the mouse genome lie in conserved syntenic segments [Waterstone et al, Nature 420, 2002] Ksenia Krasheninnikova (AU) Human-Mouse Synteny September 18, / 20
5 Synteny What is a synteny block? A block of genes (markers) with evolutionary conserved order [cinteny.cchmc.org] Segments that can be converted into conserved segments by micro-rearrangements Usually consists of short regions of similarity (anchors) that may be interrupted by dissimilar regions and gaps [Pavel Pevzner and Glenn Tesler, 2003] Ksenia Krasheninnikova (AU) Human-Mouse Synteny September 18, / 20
6 Genetic Properties of Locuses: Two Strategies 1 first get genome pairwise alignments and use them as anchors to find synteny blocks Alignments: BLASTZ (local), Vista(glocal) Algorithms: GRIMM-Synteny, DRIMM-Synteny, i-adhore 2 get synteny mark-up from database and align syntenic regions to get 1-nucleotide resolution Databases: Cinteny, OrthoClusterDB Ksenia Krasheninnikova (AU) Human-Mouse Synteny September 18, / 20
7 Algorithms GRIMM-Synteny: given anchors Anchor graph, gap size G search for connected components i-adhore given anchors genomic profiles represent alignmnets of homologous segments greedy algorithm used to construct the alignments Ksenia Krasheninnikova (AU) Human-Mouse Synteny September 18, / 20
8 Alignments and Coverage BLASTZ Whole genome-genome local alignment adjusted for complicated genomes comparison Repeat masking Specialized substitution matrix Coverage: 32.5% VISTA Whole genome-genome alignment Pipeline: BLAT local alignments Shuffle-LAGAN glocal chaining Sensible to inversions Coverage: 7-20% Ksenia Krasheninnikova (AU) Human-Mouse Synteny September 18, / 20
9 Transcription Start Sites (TSS) Coverage Transcription Start Site is where a molecule of RNA polymerase II binds. The start site is where transcription of the gene into RNA begins. Figure : Start of transcription, yellow ellipse shows the RNA polymerase II Ksenia Krasheninnikova (AU) Human-Mouse Synteny September 18, / 20
10 Transcription Start Sites (TSS) Coverage TSS can be treated as an exact position in genome or also as a location area UCSC Genome Browser Data: SwitchGear TSS and Eponine TSS (Experimental and Machine Learning approaches) alternative: txstart or segment around cdsstart Ksenia Krasheninnikova (AU) Human-Mouse Synteny September 18, / 20
11 Distribution of the conservative TSSs for txstart locus [UCSC Genome Browser Data] Figure : Cumulative frequency of conservation between TSS regions in Human-Mouse for a genome segment [txstart-50, txstart] Figure : Cumulative frequency of conservation between the closest TSS regions in Human-Mouse for a genome segment [txstart-50, txstart+50] Ksenia Krasheninnikova (AU) Human-Mouse Synteny September 18, / 20
12 Distribution of conservation of TSS for [cdsstart - X, cdsstart] locus [UCSC Genome Browser Data] Figure : Cumulative frequency of conservation between the TSS regions in Human-Mouse for a genome segment [cdsstart-35, cdsstart] Figure : Cumulative frequency of conservation between the Human TSS and Mouse Genome for a genome segment [cdsstart-50, cdsstart] Ksenia Krasheninnikova (AU) Human-Mouse Synteny September 18, / 20
13 Is it expected to be conserved? Figure : Phylogeny and constrained elements from the 29 eutherian mammalian genome sequences. Ksenia Krasheninnikova (AU) Human-Mouse Synteny September 18, / 20
14 Highly Conserved TSS 4748 tss: txstart(mouse) txstart(human) < 100. Figure : Frequency of distance between the closest TSS in Human-Mouse Figure : Cumulative distribution for distance [0, 2000], step = 100 Ksenia Krasheninnikova (AU) Human-Mouse Synteny September 18, / 20
15 Expression of genes closest to the highly conserved TSS according to RefSeq Figure : Expression in kidneys red - low-distance tss blue - large-distance tss Figure : Expression in lungs Ksenia Krasheninnikova (AU) Human-Mouse Synteny September 18, / 20
16 Expression of genes closest to the highly conserved TSS according to RefSeq Figure : Expression in liver red - low-distance tss blue - large-distance tss Figure : Expression in hypothalamus Ksenia Krasheninnikova (AU) Human-Mouse Synteny September 18, / 20
17 Statistical difference in expression of genes close to low-distance tss comparing to large-distance tss Wilcoxon rank-sum test : Lungs: p-value = Kidney: p-value = 3.713e-09 Hypothalamus: p-value = Ksenia Krasheninnikova (AU) Human-Mouse Synteny September 18, / 20
18 Statistical difference in expression of genes close to low-distance tss comparing to large-distance tss Wilcoxon rank-sum test : Lungs: p-value = Kidney: p-value = 3.713e-09 Hypothalamus: p-value = Alternative hypothesis: one distribution is stochastically greater than the other Ksenia Krasheninnikova (AU) Human-Mouse Synteny September 18, / 20
19 However What does the Human - Mouse 90% similarity suggest? Figure : Alignment of the 1st human chromosome against the 1st mouse chromosome [GRIMM Human-Mouse alignments at cinteny.cchmc.org] Figure : Genes in the large green region [GRIMM Human-Mouse alignments at cinteny.cchmc.org] Ksenia Krasheninnikova (AU) Human-Mouse Synteny September 18, / 20
20 Discussion Thank you! Ksenia Krasheninnikova (AU) Human-Mouse Synteny September 18, / 20
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
Heuristics for the Sorting by Length-Weighted Inversions Problem on Signed Permutations
Heuristics for the Sorting by Length-Weighted Inversions Problem on Signed Permutations AlCoB 2014 First International Conference on Algorithms for Computational Biology Thiago da Silva Arruda Institute
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
GMQL Functional Comparison with BEDTools and BEDOPS
GMQL Functional Comparison with BEDTools and BEDOPS Genomic Computing Group Dipartimento di Elettronica, Informazione e Bioingegneria Politecnico di Milano This document presents a functional comparison
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,
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
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,
Yale Pseudogene Analysis as part of GENCODE Project
Sanger Center 2009.01.20, 11:20-11:40 Mark B Gerstein Yale Illustra(on from Gerstein & Zheng (2006). Sci Am. (c) Mark Gerstein, 2002, (c) Yale, 1 1Lectures.GersteinLab.org 2007bioinfo.mbb.yale.edu Yale
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
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
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
Pairwise Sequence Alignment
Pairwise Sequence Alignment carolin.kosiol@vetmeduni.ac.at SS 2013 Outline Pairwise sequence alignment global - Needleman Wunsch Gotoh algorithm local - Smith Waterman algorithm BLAST - heuristics What
Protein & DNA Sequence Analysis. Bobbie-Jo Webb-Robertson May 3, 2004
Protein & DNA Sequence Analysis Bobbie-Jo Webb-Robertson May 3, 2004 Sequence Analysis Anything connected to identifying higher biological meaning out of raw sequence data. 2 Genomic & Proteomic Data Sequence
Tutorial. Reference Genome Tracks. Sample to Insight. November 27, 2015
Reference Genome Tracks November 27, 2015 Sample to Insight CLC bio, a QIAGEN Company Silkeborgvej 2 Prismet 8000 Aarhus C Denmark Telephone: +45 70 22 32 44 www.clcbio.com support-clcbio@qiagen.com Reference
Efficient Parallel Execution of Sequence Similarity Analysis Via Dynamic Load Balancing
Efficient Parallel Execution of Sequence Similarity Analysis Via Dynamic Load Balancing James D. Jackson Philip J. Hatcher Department of Computer Science Kingsbury Hall University of New Hampshire Durham,
arxiv:1501.07546v1 [q-bio.gn] 29 Jan 2015
![arxiv:1501.07546v1 [q-bio.gn] 29 Jan 2015](/thumbs/39/18167127.jpg "arxiv:1501.07546v1 [q-bio.gn] 29 Jan 2015")
A Computational Method for the Rate Estimation of Evolutionary Transpositions Nikita Alexeev 1,2, Rustem Aidagulov 3, and Max A. Alekseyev 1, 1 Computational Biology Institute, George Washington University,
Module 1. Sequence Formats and Retrieval. Charles Steward
The Open Door Workshop Module 1 Sequence Formats and Retrieval Charles Steward 1 Aims Acquaint you with different file formats and associated annotations. Introduce different nucleotide and protein databases.
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
Activity 7.21 Transcription factors
Purpose To consolidate understanding of protein synthesis. To explain the role of transcription factors and hormones in switching genes on and off. Play the transcription initiation complex game Regulation
Worksheet - COMPARATIVE MAPPING 1
Worksheet - COMPARATIVE MAPPING 1 The arrangement of genes and other DNA markers is compared between species in Comparative genome mapping. As early as 1915, the geneticist J.B.S Haldane reported that
Gene mutation and molecular medicine Chapter 15
Gene mutation and molecular medicine Chapter 15 Lecture Objectives What Are Mutations? How Are DNA Molecules and Mutations Analyzed? How Do Defective Proteins Lead to Diseases? What DNA Changes Lead to
A Tutorial in Genetic Sequence Classification Tools and Techniques
A Tutorial in Genetic Sequence Classification Tools and Techniques Jake Drew Data Mining CSE 8331 Southern Methodist University jakemdrew@gmail.com www.jakemdrew.com Sequence Characters IUPAC nucleotide
Thymine = orange Adenine = dark green Guanine = purple Cytosine = yellow Uracil = brown
1 DNA Coloring - Transcription & Translation Transcription RNA, Ribonucleic Acid is very similar to DNA. RNA normally exists as a single strand (and not the double stranded double helix of DNA). It contains
Genome Explorer For Comparative Genome Analysis
Genome Explorer For Comparative Genome Analysis Jenn Conn 1, Jo L. Dicks 1 and Ian N. Roberts 2 Abstract Genome Explorer brings together the tools required to build and compare phylogenies from both sequence
Scottish Qualifications Authority
National Unit specification: general information Unit code: FH2G 12 Superclass: RH Publication date: March 2011 Source: Scottish Qualifications Authority Version: 01 Summary This Unit is a mandatory Unit
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
Chapter 6 DNA Replication
Chapter 6 DNA Replication Each strand of the DNA double helix contains a sequence of nucleotides that is exactly complementary to the nucleotide sequence of its partner strand. Each strand can therefore
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
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
FINDING RELATION BETWEEN AGING AND
FINDING RELATION BETWEEN AGING AND TELOMERE BY APRIORI AND DECISION TREE Jieun Sung 1, Youngshin Joo, and Taeseon Yoon 1 Department of National Science, Hankuk Academy of Foreign Studies, Yong-In, Republic
Module 3. Genome Browsing. Using Web Browsers to View Genome Annota4on. Kers4n Howe Wellcome Trust Sanger Ins4tute zfish- help@sanger.ac.
Module 3 Genome Browsing Using Web Browsers to View Genome Annota4on Kers4n Howe Wellcome Trust Sanger Ins4tute zfish- help@sanger.ac.uk Introduc.on Genome browsing The Ensembl gene set Guided examples
Analysis of ChIP-seq data in Galaxy
Analysis of ChIP-seq data in Galaxy November, 2012 Local copy: https://galaxy.wi.mit.edu/ Joint project between BaRC and IT Main site: http://main.g2.bx.psu.edu/ 1 Font Conventions Bold and blue refers
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
Note: This document wh_informatics_practical.doc and supporting materials can be downloaded at
Woods Hole Zebrafish Genetics and Development Bioinformatics/Genomics Lab Ian Woods Note: This document wh_informatics_practical.doc and supporting materials can be downloaded at http://faculty.ithaca.edu/iwoods/docs/wh/
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
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
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
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
SICKLE CELL ANEMIA & THE HEMOGLOBIN GENE TEACHER S GUIDE
AP Biology Date SICKLE CELL ANEMIA & THE HEMOGLOBIN GENE TEACHER S GUIDE LEARNING OBJECTIVES Students will gain an appreciation of the physical effects of sickle cell anemia, its prevalence in the population,
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.
Mapping bias overestimates reference allele frequencies at the HLA genes in the 1000 Genomes Project phase I data
Mapping bias overestimates reference allele frequencies at the HLA genes in the 1000 Genomes Project phase I data Débora Y. C. Brandt*, Vitor R. C. Aguiar*, Bárbara D. Bitarello*, Kelly Nunes*, Jérôme
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
Molecular Computing. david.wishart@ualberta.ca 3-41 Athabasca Hall Sept. 30, 2013
Molecular Computing david.wishart@ualberta.ca 3-41 Athabasca Hall Sept. 30, 2013 What Was The World s First Computer? The World s First Computer? ENIAC - 1946 Antikythera Mechanism - 80 BP Babbage Analytical
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
From DNA to Protein. Proteins. Chapter 13. Prokaryotes and Eukaryotes. The Path From Genes to Proteins. All proteins consist of polypeptide chains
Proteins From DNA to Protein Chapter 13 All proteins consist of polypeptide chains A linear sequence of amino acids Each chain corresponds to the nucleotide base sequence of a gene The Path From Genes
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
Chapter 18 Regulation of Gene Expression
Chapter 18 Regulation of Gene Expression 18.1. Gene Regulation Is Necessary By switching genes off when they are not needed, cells can prevent resources from being wasted. There should be natural selection
Next generation sequencing (NGS)
Next generation sequencing (NGS) Vijayachitra Modhukur BIIT modhukur@ut.ee 1 Bioinformatics course 11/13/12 Sequencing 2 Bioinformatics course 11/13/12 Microarrays vs NGS Sequences do not need to be known
Introduction to Bioinformatics AS 250.265 Laboratory Assignment 6
Introduction to Bioinformatics AS 250.265 Laboratory Assignment 6 In the last lab, you learned how to perform basic multiple sequence alignments. While useful in themselves for determining conserved residues
Outline. MicroRNA Bioinformatics. microrna biogenesis. short non-coding RNAs not considered in this lecture. ! Introduction
Outline MicroRNA Bioinformatics Rickard Sandberg Dept. of Cell and Molecular Biology (CMB) Karolinska Institutet! Introduction! microrna target site prediction! Useful resources 2 short non-coding RNAs
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
Human Genome and Human Genome Project. Louxin Zhang
Human Genome and Human Genome Project Louxin Zhang A Primer to Genomics Cells are the fundamental working units of every living systems. DNA is made of 4 nucleotide bases. The DNA sequence is the particular
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
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
BIO 3350: ELEMENTS OF BIOINFORMATICS PARTIALLY ONLINE SYLLABUS
BIO 3350: ELEMENTS OF BIOINFORMATICS PARTIALLY ONLINE SYLLABUS NEW YORK CITY COLLEGE OF TECHNOLOGY The City University Of New York School of Arts and Sciences Biological Sciences Department Course title:
HENIPAVIRUS ANTIBODY ESCAPE SEQUENCING REPORT
HENIPAVIRUS ANTIBODY ESCAPE SEQUENCING REPORT Kimberly Bishop Lilly 1,2, Truong Luu 1,2, Regina Cer 1,2, and LT Vishwesh Mokashi 1 1 Naval Medical Research Center, NMRC Frederick, 8400 Research Plaza,
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
Molecular typing of VTEC: from PFGE to NGS-based phylogeny
Molecular typing of VTEC: from PFGE to NGS-based phylogeny Valeria Michelacci 10th Annual Workshop of the National Reference Laboratories for E. coli in the EU Rome, November 5 th 2015 Molecular typing
GenBank, Entrez, & FASTA
GenBank, Entrez, & FASTA Nucleotide Sequence Databases First generation GenBank is a representative example started as sort of a museum to preserve knowledge of a sequence from first discovery great repositories,
Clone Manager. Getting Started
Clone Manager for Windows Professional Edition Volume 2 Alignment, Primer Operations Version 9.5 Getting Started Copyright 1994-2015 Scientific & Educational Software. All rights reserved. The software
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
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
An Overview of DNA Sequencing
An Overview of DNA Sequencing Prokaryotic DNA Plasmid http://en.wikipedia.org/wiki/image:prokaryote_cell_diagram.svg Eukaryotic DNA http://en.wikipedia.org/wiki/image:plant_cell_structure_svg.svg DNA Structure
Protein Protein Interaction Networks
Functional Pattern Mining from Genome Scale Protein Protein Interaction Networks Young-Rae Cho, Ph.D. Assistant Professor Department of Computer Science Baylor University it My Definition of Bioinformatics
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.
zpicture: Dynamic Alignment and Visualization Tool for Analyzing Conservation Profiles
Resource zpicture: Dynamic Alignment and Visualization Tool for Analyzing Conservation Profiles Ivan Ovcharenko, 1,2 Gabriela G. Loots, 2 Ross C. Hardison, 3 Webb Miller, 4,5 and Lisa Stubbs 2,6 1 Energy,
Advances in RainDance Sequence Enrichment Technology and Applications in Cancer Research. March 17, 2011 Rendez-Vous Séquençage
Advances in RainDance Sequence Enrichment Technology and Applications in Cancer Research March 17, 2011 Rendez-Vous Séquençage Presentation Overview Core Technology Review Sequence Enrichment Application
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
Genome Viewing. Module 2. Using Genome Browsers to View Annotation of the Human Genome
Module 2 Genome Viewing Using Genome Browsers to View Annotation of the Human Genome Bert Overduin, Ph.D. PANDA Coordination & Outreach EMBL - European Bioinformatics Institute Wellcome Trust Genome Campus
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
Gene Switches Teacher Information
STO-143 Gene Switches Teacher Information Summary Kit contains How do bacteria turn on and turn off genes? Students model the action of the lac operon that regulates the expression of genes essential for
Nebula A web-server for advanced ChIP-seq data analysis. Tutorial. by Valentina BOEVA
Nebula A web-server for advanced ChIP-seq data analysis Tutorial by Valentina BOEVA Content Upload data to the history pp. 5-6 Check read number and sequencing quality pp. 7-9 Visualize.BAM files in UCSC
The Human Genome Project
The Human Genome Project Brief History of the Human Genome Project Physical Chromosome Maps Genetic (or Linkage) Maps DNA Markers Sequencing and Annotating Genomic DNA What Have We learned from the HGP?
Chapter 8: Recombinant DNA 2002 by W. H. Freeman and Company Chapter 8: Recombinant DNA 2002 by W. H. Freeman and Company
Genetic engineering: humans Gene replacement therapy or gene therapy Many technical and ethical issues implications for gene pool for germ-line gene therapy what traits constitute disease rather than just
Analyzing microrna Data and Integrating mirna with Gene Expression Data in Partek Genomics Suite 6.6
Analyzing microrna Data and Integrating mirna with Gene Expression Data in Partek Genomics Suite 6.6 Overview This tutorial outlines how microrna data can be analyzed within Partek Genomics Suite. Additionally,
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
Becker Muscular Dystrophy
Muscular Dystrophy A Case Study of Positional Cloning Described by Benjamin Duchenne (1868) X-linked recessive disease causing severe muscular degeneration. 100 % penetrance X d Y affected male Frequency
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
Data Analysis for Ion Torrent Sequencing
IFU022 v140202 Research Use Only Instructions For Use Part III Data Analysis for Ion Torrent Sequencing MANUFACTURER: Multiplicom N.V. Galileilaan 18 2845 Niel Belgium Revision date: August 21, 2014 Page
From DNA to Protein
Nucleus Control center of the cell contains the genetic library encoded in the sequences of nucleotides in molecules of DNA code for the amino acid sequences of all proteins determines which specific proteins
GWASrap User Manual v1.1
GWASrap User Manual v1.1 1 / 28 Table of contents Introduction... 3 System Requirements... 3 Welcome... 3 Features... 4 Create New Run... 5 GWAS Representation... 7 GWAS Annotation... 13 GWAS Prioritization...
Tutorial for Windows and Macintosh. Preparing Your Data for NGS Alignment
Tutorial for Windows and Macintosh Preparing Your Data for NGS Alignment 2015 Gene Codes Corporation Gene Codes Corporation 775 Technology Drive, Ann Arbor, MI 48108 USA 1.800.497.4939 (USA) 1.734.769.7249
Single-Cell Whole Genome Sequencing on the C1 System: a Performance Evaluation
PN 100-9879 A1 TECHNICAL NOTE Single-Cell Whole Genome Sequencing on the C1 System: a Performance Evaluation Introduction Cancer is a dynamic evolutionary process of which intratumor genetic and phenotypic
BIOINF 525 Winter 2016 Foundations of Bioinformatics and Systems Biology http://tinyurl.com/bioinf525-w16
Course Director: Dr. Barry Grant (DCM&B, bjgrant@med.umich.edu) Description: This is a three module course covering (1) Foundations of Bioinformatics, (2) Statistics in Bioinformatics, and (3) Systems
Core Bioinformatics. Degree Type Year Semester. 4313473 Bioinformàtica/Bioinformatics OB 0 1
Core Bioinformatics 2014/2015 Code: 42397 ECTS Credits: 12 Degree Type Year Semester 4313473 Bioinformàtica/Bioinformatics OB 0 1 Contact Name: Sònia Casillas Viladerrams Email: Sonia.Casillas@uab.cat
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.
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
2. True or False? The sequence of nucleotides in the human genome is 90.9% identical from one person to the next. False (it s 99.
1. True or False? A typical chromosome can contain several hundred to several thousand genes, arranged in linear order along the DNA molecule present in the chromosome. True 2. True or False? The sequence
Typing in the NGS era: The way forward!
Typing in the NGS era: The way forward! Valeria Michelacci NGS course, June 2015 Typing from sequence data NGS-derived conventional Multi Locus Sequence Typing (University of Warwick, 7 housekeeping genes)
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
Removing Sequential Bottlenecks in Analysis of Next-Generation Sequencing Data
Removing Sequential Bottlenecks in Analysis of Next-Generation Sequencing Data Yi Wang, Gagan Agrawal, Gulcin Ozer and Kun Huang The Ohio State University HiCOMB 2014 May 19 th, Phoenix, Arizona 1 Outline
org.rn.eg.db December 16, 2015 org.rn.egaccnum is an R object that contains mappings between Entrez Gene identifiers and GenBank accession numbers.
org.rn.eg.db December 16, 2015 org.rn.egaccnum Map Entrez Gene identifiers to GenBank Accession Numbers org.rn.egaccnum is an R object that contains mappings between Entrez Gene identifiers and GenBank
Biology Final Exam Study Guide: Semester 2
Biology Final Exam Study Guide: Semester 2 Questions 1. Scientific method: What does each of these entail? Investigation and Experimentation Problem Hypothesis Methods Results/Data Discussion/Conclusion
The sequence of bases on the mrna is a code that determines the sequence of amino acids in the polypeptide being synthesized:
Module 3F Protein Synthesis So far in this unit, we have examined: How genes are transmitted from one generation to the next Where genes are located What genes are made of How genes are replicated How
Genetics Module B, Anchor 3
Genetics Module B, Anchor 3 Key Concepts: - An individual s characteristics are determines by factors that are passed from one parental generation to the next. - During gamete formation, the alleles for
Accelerated evolution of conserved noncoding sequences in the human genome
Accelerated evolution of conserved noncoding sequences in the human genome Shyam Prabhakar 1,2*, James P. Noonan 1,2*, Svante Pääbo 3 and Edward M. Rubin 1,2+ 1. US DOE Joint Genome Institute, Walnut Creek,
12.1 The Role of DNA in Heredity
12.1 The Role of DNA in Heredity Only in the last 50 years have scientists understood the role of DNA in heredity. That understanding began with the discovery of DNA s structure. In 1952, Rosalind Franklin
Comparative genomic tools and databases: providing insights into the human genome
SPOTLIGHT Comparative genomic tools and databases: providing insights into the human genome Len A. Pennacchio and Edward M. Rubin Genome Sciences Department, Lawrence Berkeley National Laboratory, Berkeley,
Bob Jesberg. Boston, MA April 3, 2014
DNA, Replication and Transcription Bob Jesberg NSTA Conference Boston, MA April 3, 2014 1 Workshop Agenda Looking at DNA and Forensics The DNA, Replication i and Transcription i Set DNA Ladder The Double
Von Mäusen und Menschen E - 1
Von Mäusen und Menschen E - 1 Mus musculus: Genetic Portrait of the House Mouse E - 3 Outline Mouse genome Mouse life cycle Transgenic protocols Addition of genes by nuclear injection Removal of genes