Opportunity Description

This is an opportunity to learn some of the computational and bioinformatic tools used in genomics.

The project is to study the genetic basis of evolutionary adaptation using whole genome sequence data and functional genomic data (RNA-seq). The study system is a pair of coastal fish species in the genus Fundulus that inhabit a wide range of salinities. A probable chromosomal inversion exists which is shared by the two species, associated with environmental salinity and encompasses a critical osmoregulatory gene. The project will confirm the presence of the inversion and analyze genetic and gene expression data from genes it encompasses from multiple populations of each species.

The work is entirely computational in nature, as the data have already been collected. The student would be expected to learn the basics of analyzing genetic variation data, gene expression data, and identifying structural variants from whole genome sequence data.

The expected time commitment would be 10-15 hours per week. Taking the project to completion would likely require two semesters.

Student Qualifications
Applicants should have some prior experience using the linux command line interface, and ideally some experience with the statistical computing language R. Prior coursework should include genetics.

How to Apply
Available immediately.

Please contact Noah Reid at noah.reid@uconn.edu

Applicants should submit a resume, and explain relevant coursework and prior experience related to bioinformatics (e.g. experience using command line interfaces, scripting languages, etc).

Mentor: Noah Reid, Assistant Research Professor
Department: Molecular and Cell Biology
Email: noah.reid@uconn.edu
Timing: Spring 2019
Campus: Storrs

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