Investigating the landscape of meiotic crossovers on the chromosome through computer vision
Abby Dernburg, Professor
Molecular and Cell Biology
Closed. This professor is continuing with Fall 2023 apprentices on this project; no new apprentices needed for Spring 2024.
Meiosis is a specialized cell division that produces gametes with half the genome content of somatic cells. During meiosis, the two copies of each chromosome inherited from the two parents must physically pair along their lengths through a process called synapsis, in which a protein complex called the synaptonemal complex (SC) assembles between the chromosomes and “zips” them together. The SC also plays essential roles in the formation of “crossovers,” a specialized type of homologous recombination that links the chromosomes together. This project will use computational analysis of 3D microscope images to determine the number and distribution of crossover sites along each pair of chromosomes. Results from this project will expand our understanding of how crossover patterning is regulated in coordination with nuclear organization and meiotic cell cycle progression.
Qualifications: Specific role for the undergraduate (tasks and learning outcomes):
Tasks the student will undertake: Quantitative and high throughput analysis of crossover distribution on chromosomes during meiosis, using existing and customized code to analyze high-resolution 3D fluorescence imaging data (e.g., segmentation of individual chromosomes, analysis of morphological features of segmented chromosomes, quantification of the number and position of crossover sites per chromosome).
Learning outcomes: through this project the student will learn about the following topics – What is meiosis? What is the role and mechanism of crossover interference during meiosis? How do you come up with a specific scientific hypothesis and how do you test it?
Though this project is focused on computational image analysis, the student will also have the opportunity (per project needs) to learn how to (1) carry out CRISPR/Cas9-based genome editing in C. elegans, (2) perform genetics analysis, and (3) perform quantitative imaging using fluorescence microscopy (including super-resolution). Substantial contributions to conceptualization, methodology or investigation (including instrumentation, data collection or analysis) will be recognized by co-authorship, per our lab's tradition.
Specific qualifications the student should have:
This project will be a great fit for someone with a passion to apply their strong computational skills to answer important biological questions.
Proficiency in MATLAB or Python required;
Biology 1A: General Biology (or equivalent) –desirable but not essential;
We believe in the power of diversity and welcome motivated applicants from all background, especially those from historically underrepresented or underserved communities.
Day-to-day supervisor for this project: Chenshu Liu, Post-Doc
Hours: 9-11 hrs
Related website: https://www.hhmi.org/scientists/abby-f-dernburg
Related website: https://www.hhmi.org/scientists/abby-f-dernburg