NCSI: Mapping the Landscape of Alternative Polyadenylation Across the Mammalian Oocyte-to-embryo Transition

Status	Completed
Mentor Name	Katherine Lee
Mentor's XSEDE Affiliation	Research allocation
Mentor Has Been in XSEDE Community	Less than 1 year
Project Title	Mapping the Landscape of Alternative Polyadenylation Across the Mammalian Oocyte-to-embryo Transition
Summary	One of the most intriguing aspects of biological development is the transition from a differentiated oocyte to a completely totipotent embryo. Remarkably, this oocyte-to-embryo transition (OET) occurs in the absence of new transcription. Instead, gene regulation across these critical developmental stages relies on unique post-transcriptional mechanisms. This project seeks to investigate the role of alternative polyadenylation in regulating mRNA stability across the dynamic transition from oocyte to embryo in mammals, using cutting edge bioinformatic tools for analyzing big data from RNA-seq.
Job Description	The student’s tasks include, independently and/or under guidance, (1) compiling programs and running applications on XSEDE HPC resources; (2) developing pipelines to analyze alternative polyadenylation, mRNA stability, and sequence motif enrichment. This job involves gaining hands on experiences of running and troubleshooting commonly available bioinformatic tools for RNA-seq data analysis, as well as cutting-edge tools not previously piloted in our lab. The student is expected to have some experience coding in R, python, and bash, and/or independently learn these programming languages.
Computational Resources	The student will have access to HPC computational resources available through our lab’s XSEDE research allocation, including Bridges-2 and Expanse, as well as the Triton Shared Computing Cluster (TSCC) here at UC San Diego.
Contribution to Community	The analyses for this project will provide, for the first time, a comprehensive map of APA across the mammalian OET. Identification of stage-specific changes in 3’UTR sequence motifs and mRNA stability will provide exciting insights into the post-transcriptional gene regulatory mechanisms driving the dynamic transition from oocyte to embryo in mammals and open exciting new avenues for mechanistic studies. Further, this work will prepare and develop students for future work in bioinformatics and data science, especially in the context of modern HPC.
Position Type	Apprentice
Training Plan	The mentor will play a semi-hands-on role with the student, bringing them up-to-speed on the latest best practices in HPC computing, as well as standard and cutting-edge RNA-seq processing and analysis tools. Additionally, the student will be trained on how to think critically about science, how to write a paper, and communicate science effectively.
Student Prerequisites/Conditions/Qualifications	Programming skills, critical thinking skills, writing skills
Duration	Semester
Start Date	01/03/2022
End Date	05/01/2022