PhD Defense by Lijiang Long

Event Details
  • Date/Time:
    • Wednesday October 21, 2020
      2:00 pm - 4:00 pm
  • Location: REMOTE: BLUE JEANS
  • Phone:
  • URL: BlueJeans Link
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  • Fee(s):
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Summaries

Summary Sentence: QUANTITATIVE METHODS TO UNDERSTAND REPRODUCTIVE ISOLATIONS THAT CONTRIBUTE TO SPECIATION

Full Summary: No summary paragraph submitted.

In partial fulfillment of the requirements for the degree of 

Doctor of Philosophy in Quantitative Biosciences

in the School of Biological Sciences

 

Lijiang Long

Defends his thesis:
QUANTITATIVE METHODS TO UNDERSTAND REPRODUCTIVE ISOLATIONS THAT CONTRIBUTE TO SPECIATION

Wednesday, October 21, 2020
2:00pm Eastern Time
Via BlueJeans: https://bluejeans.com/1911724485

Advisor:

Dr. Patrick T. McGrath

School of Biological Sciences & School of Physics

Georgia Institute of Technology
Open to the Community


Committee Members:
Dr. Jeffery T. Streelman; School of Biological Sciences, Georgia Tech
Dr. Annalise Paaby; School of Biological Sciences, Georgia Tech
Dr. Greg Gibson; School of Biological Sciences, Georgia Tech
Dr. Peng Qiu; School of Biomedical Engineering, Georgia Tech

Abstract:

Ever since Darwin’s qualitative theory of the origin of species, there is growing demand for quantitative methods to study mechanisms underlying the speciation process. One key component towards new species formation is reproductive isolation. In this talk, I will present novel quantitative methods developed to study two aspects of reproductive isolation: automated measurement of species-specific social behavior in Lake Malawi cichlids, quantitative measurement of the fitness of a toxin-antidote element (a special type of Dobzhansky-Muller site) in C. elegans and modeling and/or simulations to understand the evolution of both toxin-antidote element and the rest of the genome in silico. First, variations in bower type (‘pits’ and ‘castles’) is one important mechanism to create reproductive barrier and maintain a large number of cichlids species in Lake Malawi. To understand the biological basis of these behaviors, an automatic behavior quantification pipeline was built. Each action video clip was classified into ten categories using a 3D Residual Network (3D ResNet). These ten categories distinguish spitting, scooping, fin swipes and spawning. I showed that this approach is accurate (> 76% accuracy) in distinguishing fish behaviors. Next, I will talk about quantitative methods to study the ability of selfish genetic elements to spread in populations. Pair-wise competition assays showed the loss of the toxin gene peel-1 decreased fitness of hermaphrodites, contradicting my expectation that peel-1 will decrease animal fitness due to its toxicity. This fitness advantage is independent of the antidote gene zeel-1.  This work showed that toxin-antidote systems can spread through populations independent of their selfish effects. Finally, I use simulation methods to study the effect of toxin-antidote elements on linked and unlinked genetic variation in the case of admixture. I will show that unlinked neutral genetic variants will increase their frequency when their frequency is higher than 1/3 and decrease when they started lower than 1/3. My doctoral thesis with many quantitative methods will advance our understanding of the genetic basis of species evolution and evolutional dynamics of selfish genetic elements.

Additional Information

In Campus Calendar
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Graduate Studies

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Faculty/Staff, Public, Graduate students, Undergraduate students
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Other/Miscellaneous
Keywords
Phd Defense
Status
  • Created By: Tatianna Richardson
  • Workflow Status: Published
  • Created On: Oct 7, 2020 - 11:37am
  • Last Updated: Oct 7, 2020 - 11:37am