BIOL200 2013: Difference between revisions

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| Evolution can be defined as descent with modification.  In other words, changes in the nucleotide sequence of an organsim’s genomic DNA is inherited by the next generation.  According to this, all organisms are related through descent from an ancestor that lived in the distant past.  Since that time, about 4 billion years ago, life has undergone an extensive process of change as new kinds of organisms arose from other kinds existing in the past.<br /> The evolutionary history of a group is called a phylogeny, and can be represented by a phylogram (Figure 1).  A major goal of evolutionary analysis is to understand this history.  We do not have direct knowledge of the path of evolution, as by definition, extinct organisms no longer exist.  Therefore, phylogeny must be inferred indirectly.  Originally, evolutionary analysis was based upon the organisms’ morphology and metabolism.  This is the basis for the Linnaean classification scheme (the “Five Kingdoms” scheme).  However, this method can lead to mistaken relationships.  Different species living in the same environment may have similar morphologies in order to deal with specific environmental factors.  Thus these similarities have nothing to do with how related the organisms are, but are a direct result of shared surroundings.  However, with the advent of genomics, organisms can be grouped based upon their sequence relatedness.  Since evolution is a process of inherited nucleotide change, analyzing DNA sequence differences allows for the reconstruction of a better phylogenetic history.<br/>
| Evolution can be defined as descent with modification.  In other words, changes in the nucleotide sequence of an organsim’s genomic DNA is inherited by the next generation.  According to this, all organisms are related through descent from an ancestor that lived in the distant past.  Since that time, about 4 billion years ago, life has undergone an extensive process of change as new kinds of organisms arose from other kinds existing in the past.<br /> The evolutionary history of a group is called a phylogeny, and can be represented by a phylogram (Figure 1).  A major goal of evolutionary analysis is to understand this history.  We do not have direct knowledge of the path of evolution, as by definition, extinct organisms no longer exist.  Therefore, phylogeny must be inferred indirectly.  Originally, evolutionary analysis was based upon the organisms’ morphology and metabolism.  This is the basis for the Linnaean classification scheme (the “Five Kingdoms” scheme).  However, this method can lead to mistaken relationships.  Different species living in the same environment may have similar morphologies in order to deal with specific environmental factors.  Thus these similarities have nothing to do with how related the organisms are, but are a direct result of shared surroundings.  However, with the advent of genomics, organisms can be grouped based upon their sequence relatedness.  Since evolution is a process of inherited nucleotide change, analyzing DNA sequence differences allows for the reconstruction of a better phylogenetic history.<br/>
|-
|-
[[File:TreeLife.png|thumb|center|alt= The Tree of Life.|Tree of life based on 16S ribosomal RNA (image credit: NR Pace, Science 1997).]]
|[[File:TreeLife.png|thumb|center|alt= The Tree of Life.|Tree of life based on 16S ribosomal RNA (image credit: NR Pace, Science 1997).]]
#Display the absolute path of your home directory
|Of course, when comparing DNA sequences, the question of which genes to use arises.  The most widely used genes are those coding for the 16S rRNA gene in prokaryotes and the 18S rRNA gene in eukaryotes. These genes code for small subunit ribosomal RNA and are used for evolutionary analysis because they 1) are found in all organisms, 2) are functionally conserved, 3) vary only slightly between organisms (their nucleotide sequence changed slowly throughout evolution), and 4) have adequate length. In this lab, you will be performing evolutionary analysis by constructing a phylogram of 15 microbes spanning bacteria, archaea and eukarya. You will find and download rRNA sequences, align them and use that alignment to create a phylogram.
#List files in your home directory in long format & ordered by their time stamps
#List files in the "/data/yoda/b/student.accounts/bio425_2011/" directory from your home directory
#Copy of the file "/data/yoda/b/student.accounts/bio425_2011/data/GBB.seq" into your home directory
#Count the number of lines in the file "GBB.seq"
#Show the first five lines of the file "GBB.seq" & save it to a file with arbitrary name
#Show your last ten commands using "history"
|-style="background-color:powderblue;"
| '''Read''' Chapter 1
|}
|}



Revision as of 16:00, 4 March 2013

EXPERIMENT # 4

BIOL 200 Cell Biology II LAB, Spring 2013

Hunter College of the City University of New York

Course information

Instructors: TBD

Class Hours: Room TBD HN; TBD

Office Hours: Room 830 HN; Thursdays 2-4pm or by appointment

Contact information:

  • Dr. Weigang Qiu: weigang@genectr.hunter.cuny.edu, 1-212-772-5296


Experiment #4

The Tree of Life and Molecular Identification of Microorganisms

Objective

To classify microorganisms and determine their relatedness using molecular sequences.

LAB REPORT GRADING GUIDE

CELL BIO II Experiment #4:

  • Introduction 1 point :
 Statement of objectives or aims of the experiment in the student’s own words.
 (not to be copied from the Lab Manual)
  • MATERIALS AND METHODS 0 points :
 This should be a brief synopsis and must include any changes or deviations 
 from the procedures outlined in the Lab Manual. Specify which organisms were 
 used to create the phylogram.
  • RESULTS 4 points :
 A print out of the phylogram will suffice.
  • DISCUSSION 4 points :
 Responses to discussion questions.
  • SUMMARY |CONCLUSION 1 point :
 Two sentence summary of your findings.
  • REFERENCES 1 point :
 Credit is given for pertinent references obtained from sources other than the Lab Manual.
 This point is in addition to the 10 for the lab report..

INTRODUCTION

February 5

February 12

NO CLASS

(Read Chapter 6 for next class)

February 19

Yozen will not be lecturing

  • Chapter 6. Gene and Genome Structures [Lecture Slides Lecture Slides Ch.6-Che
  • Tutorial: ORF Prediction using GLIMMER
  • Homework: This homework will be graded.

February 26

March 5

March 12

March 19

  • REVIEW Session for MID-TERM EXAMS

March 26

  • MID-TERM

April 2

April 9

April 16

  • Topic: Relational Database and SQL
  • Tutorial: the Borrelia Genome Database
  • Homework: SQL-embedded PERL

April 23

NO CLASSES (Spring recess)

April 30

May 7

  • Chapter 6 (Gene Expression) & Chapter 8 (Proteomics)
  • Tutorial: Array Data Visualization and Analysis ( Micro-Array Analysis Slides)
  • Homework:Data Analysis using R

May 14

  • Chapter 7. Protein Structure Prediction

May 21

  • Final Project Due (TBA)

Useful Links

Unix Tutorials

Perl Help

  • Professor Stewart Weiss has taught CSCI132, a UNIX and Perl class. His slides go into much greater detail and are an invaluable resource. They can be found on his course page here.
  • Perl documentation at perldoc.perl.org. Besides that, running the perldoc command before either a function (with the -f option ie, perldoc -f substr) or a perl module (ie, perldoc Bio::Seq) can get you similar results without having to leave the terminal.

Bioperl

SQL

R Project

  • Install location and instructions for Windows
  • Install location and instructions for Mac OS X
  • For users of Ubuntu/Debian:
sudo apt-get install r-base-core
  • For users of Fedora/Red Hat:
su -
yum install R

Utilities

Other Resources


© Weigang Qiu, Hunter College, Last Update Jan 2013