NORTH CAROLINA STATE UNIVERSITY
GRADUATE COURSE ACTION FORM
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TYPE OF PROPOSAL
DEPARTMENT/PROGRAM
PLANT PATHOLOGY
COURSE PREFIX/NUMBER
PP (MB) 715
PREVIOUS PREFIX/NUMBER
PP 610W/810W
DATE OF LAST ACTION
NA
COURSE TITLE
Applied Evolutionary Analysis of Population Genetic Data
ABBREVIATED TITLE
APPL EVOL POPN GEN
SCHEDULING
Fall
Spring
Alt. Year Odd
COURSE OFFERED
CREDIT HOURS
CONTACT HOURS
Studio
New Course
Drop Course
Course Revision
Dual-Level Course
REVISION
Content
Prefix/Number
Title
Abbreviated Title
Credit Hours
Contact Hours
Grading Method
Pre-Corequisites
Restrictive Statement
Description
Scheduling
Summer
Every Year
Alt. Year Even
Other
BY DISTANCE EDUCATION ONLY
ON CAMPUS ONLY
BOTH ON CAMPUS AND BY DISTANCE EDUCATION
3
Lecture/Recitation 2 Seminar
Independent Study/Research
Laboratory
Problem 1
Internship/Practicum/Field Work
GRADING
ABCDF
S/U
INSTRUCTOR (NAME/RANK)
Ignazio Carbone/Assistant Professor
Graduate Faculty Status Associate
ANTICIPATED ENROLLMENT
Per semester 15
PREREQUISITE(S)
PP 707, GN 703, ST 501
COREQUISITE(S)
type course numbers here
PRE/COREQUISITE FOR
type course number(s) here
RESTRICTIVE STATEMENT
type BRIEF statement here
CURRICULA/MINORS
Required
Qualified Elective
type program name here
type elective name here
PROPOSED EFFECTIVE DATE
August 2007
Max.Section 20
Full
Multiple sections Yes
No
APPROVED EFFECTIVE DATE __________________________
CATALOG DESCRIPTION (limit to 80 words):
This course will introduce nonparametric and model-based methods for making inferences on population processes (mutation, migration,
drift, recombination, and selection). The goal is to provide a conceptual overview of these methods and hands-on training on how to
implement and interpret the results. Sample data sets in computer laboratories will integrate summary statistic, cladistic, coalescent, and
bayesian approaches to examine population processes in different pathosystems with specific emphasis on eukaryotic microbes, viruses and
bacteria.
DOCUMENTATION AS REQUIRED
Please number all document pages
RECOMMENDED BY:
_______________________________________________________________________
Department Head/Director of Graduate Programs
Date
Course Justification
Proposed Revision(s) with
Justification
Student Learning Objectives
Enrollment for Last 5 Years
ENDORSED BY:
_______________________________________________________________________
Chair, College Graduate Studies Committee
Date
New Resources Statement
Consultation with other Departments
Syllabus (Old and New)
Explanation of differences in
requirements of dual-level courses
________________________________________________________________________
College Dean(s)
Date
APPROVED:
______________
_______________________________________________________
1
____
Dean of the Graduate School
Date
2
COURSE JUSTIFICATION
Genomes are dynamic and evolving units. Their present organization and function is the
result of evolutionary forces that are acting on individuals in populations over time. This course
is designed to provide an advanced understanding of evolutionary tools, their specific
assumptions, limitations and power. Some of the topics covered include molecular marker
selection and their utility in evolutionary analysis, approaches for biological data integration and
analysis, cladistic methods for biological inference, population parameter estimation and
hypothesis testing using summary statistic, coalescent and Bayesian models. This course will be
organized into lectures and computer laboratories (problem periods). Lectures will introduce
evolutionary concepts and laboratories will provide hands-on training with the tools. The focus
will be on applying these concepts and tools to understand evolutionary processes in eukaryotic
microbes, viruses and bacteria. Students will have the opportunity to analyze their own
molecular data sets or work through previously published data sets using new tools and
methodologies. The evolutionary approaches that will be examined in this course are inherently
rich in mathematical concepts, statistics and population genetics theory. Students will gain a
better understanding of these concepts by applying these methods to real data sets.
STUDENT LEARNING OBJECTIVES
This course will provide students with:
1.
Hands-on training on a diverse set of tools implemented in the SNAP Workbench
evolutionary toolkit (http://snap.cifr.ncsu.edu). Among these are Hudson’s haplotype and
sequence-based statistics, MDIV and IM (isolation models), migrate-n (island models),
Genetree (infinite sites and stepwise mutation models), RecMin, recom58, fins, LDhat,
shrub, HapBound, beagle, and LAMARC.
2.
Step-by-step analysis and interpretation of sample data sets.
opportunity to analyze their own data set.
3.
A foundation in the use of SNAP Workbench to allow for further integration of new
methods for estimating population parameters.
4.
An understanding of the power, limitations and assumptions of summary statistic,
cladistic, coalescent, and bayesian approaches in evolutionary population genetic analysis.
5.
Criteria for molecular marker selection and their utility in evolutionary analysis.
6.
Genealogical-based approaches for integrating molecular genetic and phenotypic data.
7.
Experience in data analysis, interpretation, written and oral presentation.
Students will have the
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SYLLABUS
PP715-Applied Evolutionary Analysis of Population Genetic Data
Fall 2007
Location: Room 105b located in Toxicology Building, Centennial Campus
Meeting Day and Time: Friday, 9:00AM-12:00PM
Instructor: Dr. Ignazio Carbone
E-mail: ignazio_carbone@ncsu.edu
Office: Partners III Building, Room 229
Phone: 513-4866
Office Hours: By appointment
Prerequisites: PP707, GN 703, ST 501
REQUIRED TEXT
No text is required for this course. Suggested readings will be made available for each lecture
topic online by logging into the Vista site (http://vista.ncsu.edu). Copies of the syllabus and class
notes will be available in the classroom and online after the lecture.
GRADING
One Exam
One 15 min Oral Presentation
One Research Paper
Class Participation and Discussion
30%
30%
30%
10%
Oral presentations will allow students to build on their knowledge of concepts introduced in
lectures and labs by analyzing a published dataset (provided by the instructor) for the presence
and magnitude of a specific evolutionary force. This will require students to integrate
nonparametric and parametric methods implemented in the workbench and to interpret their
results with specific emphasis on the biological inferences and the assumptions and limitations of
the selected methods.
Research papers will require students to integrate all tools and methodologies presented in the
course to analyze their own molecular dataset or select one provided by the instructor. Research
papers will follow scientific format and include tables, figures and references.
FINAL GRADES
Final grade submitted will be based on the following grade scale; 100-98=A+, 97.9-91=A, 90.989=A-, 88.9-87=B+, 86.9-81=B, 80.9-79=B-, 78.9-77=C+, 76.9-71=C, 70.9-69=C-, 68.9-67=D+,
66.9-61=D, 60.9-59=D-, Below 59=F
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ATTENDANCE POLICY
Attendance will not be taken. Students are responsible for attending and for learning the material
provided in both lecture and computer laboratory. If a class is missed, it is the students'
responsibility to obtain lecture notes and handouts on their own. The instructor will not provide
lecture notes to students.
ACADEMIC INTEGRITY
All students are required to adhere to the NC State University's Code of Student Conduct. The
text of this code may be obtained from the instructor or is available online at:
(http://www.ncsu.edu/student_conduct).
STATEMENT FOR STUDENTS WITH DISABILITIES:
" Reasonable accommodations will be made for students with verifiable disabilities. In order to
take advantage of available accommodations, students must register with Disability Services for
Students at 1900 Student Health Center, Campus Box 7509, 515-7653. For more information on
NC State's policy on working with students with disabilities, please see the Academic
Accommodations for Students with Disabilities Regulation (REG02.20.1):
http://www.ncsu.edu/policies/academic_affairs/courses_undergrad/REG02.20.1.php
ENROLLMENT LAST 5 YEARS
This course was taught in Fall 2003 and Fall 2005 as a Special Topics Course.
Fall 2003 – PP610W/810W – 1 credit hour – 8 students enrolled
Fall 2005 – PP610W/810W – 3 credit hours – 13 students enrolled (10 PhD students)
NEW RESOURCES REQUIRED
No new resources required. Computer lab in Toxicology 105b is available for use.
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PP715 Schedule
Lecture
Topic
Suggested Reading
1, 2
Introduction:
Theoretical Population Genetics with focus on
eukaryotic microbes, viruses and bacteria
Wakeley (2005)
Pluzhnikov & Donnelly
(1996)
3, 4
Population Structure I:
Evolutionary Framework
Hey and Machado (2003)
Price and Carbone (2005)
5, 6
Population Structure II:
Summary Statistics
Neutrality Tests
a priori Inference
Tajima (1989a)
Tajima (1989b)
Fu and Li (1993)
Fu (1997)
7, 8
Population Structure III:
Intraspecific Phylogenetic Reconstruction
Compatibility and Recombination Blocks
Network Inference
Koopman (2005)
Cassens et al. (2005)
Jakobsen et al. (1997)
Myers and Griffiths (2003)
Exam, 9
Population Structure IV:
Nested Cladistic Analysis
Phylogeography
Haplotype-phenotype Association Biological
Inference
Knowles & Maddison (2002)
Hudson et al. (1992)
Templeton (1998)
Hare (2001)
10, 11
Population Processes I:
Coalescent Models
(panmixia, recombination)
Genealogical Inference
Hudson (1990)
Rosenberg & Nordborg
(2002)
Griffiths & Marjoram (1996)
12, 13
Population Processes II:
Coalescent Models
(subdivision)
Genealogical Inference
Bahlo and Griffiths (2000)
Carbone et al. (2004)
Fall Break
14, 15
Tools for Single Locus Inferences
Example from viruses
Carbone et al. (2004)
16, 17
Tools for Multilocus Inferences
Examples from viruses and fungi
Carbone et al. (1999)
Carbone et al. (2004)
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18, 19
Methods in Testing for Population Subdivision
Oral Presentations
Hudson (2000)
20, 21
Tools for Multilocus Estimates of Recombination
Rates
Oral Presentations
Fearnhead and Donnelly
(2001)
22, 23
Multilocus Estimates of Migration Rates, Effective
Population Sizes and Divergence Time
Oral Presentations
Hey and Nielsen (2004)
24, 25
Simultaneous Estimation of Migration and
Recombination
Oral Presentations
Beerli and Felsenstein (2001)
Thanksgiving Holiday – No class
26
Synthesis and Course Evaluation
Research Paper Due
7
From: Gerry Luginbuhl <Gerry_Luginbuhl@ncsu.edu>
Date: Tue, 20 Dec 2005 16:41:12 -0500
To: <ignazio_carbone@ncsu.edu>
Subject: PP710
Ignazio,
The Graduate Curriculum Committee in the Department of Microbiology has
reviewed the syllabus for PP710 and your request for cross-listing this course in
Microbiology. From the syllabus provided, the committee viewed the content of
the course as focusing on the computational methods of evolutionary analysis
of genomes. This is a relevant topic for Microbiology students to pursue and
given the breadth of interests in the graduate program it would be a suitable
elective course for some students. However, while the example course study
papers you provided were interesting and relevant, it is the syllabus and course
description that are first available to prospective students for determining the
focus and relevance of the course. To better assist Microbiology graduate
students in appreciating what you identified as the skew of the course in
applying these concepts to eukaryotic microbes, viruses, and even bacteria,
these elements could be presented in the course description and in the
syllabus. With that recommendation, the Department of Microbiology approves
the cross-listing of this Ph.D. level course. You should be aware that MB 710,
Biological Transmission Electron Microscopy (an "on demand" graduate course)
currently uses the 710 designation so this must be considered for the MB
cross-listing.
Gerry
Gerry Luginbuhl
Interim Head
Department of Microbiology
North Carolina State University
Raleigh, NC 27695-7615
Phone: 919-515-7484
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------ Forwarded Message
From: Margaret Daub <margaret_daub@ncsu.edu>
Reply-To: <margaret_daub@ncsu.edu>
Date: Wed, 21 Dec 2005 11:29:14 -0500
To: Ignazio Carbone <ignazio_carbone@ncsu.edu>, <james_moyer@ncsu.edu>
Cc: <boston@unity.ncsu.edu>
Subject: Re: PP 710
Ignazio and Jim –
We are pleased to see the new plant pathology course offering on "Applied Evolutionary Analysis of
Population Genetic Data". It will be an attractive offering for students interested in population biology. The
Department of Botany does not offer any similar courses. We anticipate that it would be taken by a few of
our students, and that interest may increase as collaborations are established among some of our recent
hires. We support the addition of this course to the CALS curricula. We do not anticipate a need to crosslist the course with Botany at this time.
Thank you for sharing the information about this course.
Regards - Margo
***************************
Margaret E. Daub
Professor and Department Head
Department of Botany
Box 7612
North Carolina State University
Raleigh, NC 27695-7612
Phone: (919) 515-2727, 515-6986
FAX: (919) 515-3436
E-mail: margaret_daub@ncsu.edu
***************************
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------ Forwarded Message
From: Zhao-Bang Zeng <zeng@statgen.ncsu.edu>
Date: Fri, 06 Jan 2006 15:30:32 -0500
To: Ignazio Carbone <ignazio_carbone@ncsu.edu>
Cc: Barbara Sherry <barbara_sherry@ncsu.edu>
Subject: Re: PP 710
Dear Ignazio:
I have forwarded your message to BI curriculum committee and have not gotten
feedback yet. This is a very interesting and practical course for evolutionary studies on
popgen data. I am sure that some of our BI students would find it useful and your record
showed that. BI curriculum has not formally set up yet. We will discuss it as a possible
selective course for BI students in due course.
Zhao-Bang Zeng
***********************************************************************
Dr. Zhao-Bang Zeng
William Neal Reynolds Distinguished Professor
Director, Bioinformatics Research Center
Departments of Statistics & Genetics
North Carolina State University
1521 Partners II Building, 840 Main Campus Drive
Raleigh, NC 27695-7566, USA
Tel: 919 515-1942; FAX: 919 515-7315 (Attn: Zeng)
Email: zeng@stat.ncsu.edu; Home page: http://statgen.ncsu.edu/
***********************************************************************
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