The Genomics project aims to develop a detailed framework of known differentially expressed genes between S. cerevisiae strains s288c and YJM145 using a multi-omics screen. Analyzing data from RNA-sequencing (RNA-seq) and Mass Spectrometry (MS) experiments provide insight on the mechanisms of differential expression caused by various polymorphisms. Data for these experiments was gathered during steady state conditions and at multiple time points during mating pheromone response, allowing for insight into dynamic aspects of expression variation. Individual genes are then classified into specific categories of expression variation, information from which is used to provide context and/or direction for lab research. Utilizing this dataset, we also aim to provide further insight into previously collected datasets investigating natural variation between s288c and YJM145 isolates or between related strains.

Current Team: Benjamin Haagen, Noah Haight, Dan Pollard

The Local Bulked Segregant Analysis (BSA) project focuses on developing an innovative fine-mapping method to pinpoint causal polymorphisms responsible for trait variation in yeast. The case study of the Local BSA project is the CAM1/DIG1 locus which has been found through whole-genome BSA mapping to affect the protein expression levels of FIG1. By combining BSA with a novel localized recombination scheme using flanking selection markers, we aim to efficiently identify specific single nucleotide polymorphisms (SNPs) within the CAM1/DIG1 locus responsible for FIG1 protein variation. The development of this methodology will enable a deeper understanding of which and how DNA variants affect key phenotypic traits and potentially uncover new genetic mechanisms underlying trait variation.

Current Team: Minh Phan, Winter Yi, Dan Pollard

This project focuses on how natural allelic differences in the sequence of a gene can alter the abundance of RNA and protein produced by the gene. In previous work, we discovered that allelic variation in the usage of codons with more abundant cognate tRNAs (codon bias) and mRNA folding strength (mF) interact synergistically to modify protein synthesis rates in yeast. We are now expanding the project to look at effects at both the RNA and protein level as well as additional sequence features, such as mean elongation transcription rate (MTTR).

Current Team: Nadine Tietz, Dan Pollard

Genetic variants can act on protein expression either directly by modifying protein translation or decay rates or indirectly by modifying RNA transcription or decay rates. On a single cell level, protein abundances can be measured easily using fluorescence microscopy but comparable techniques for measuring RNA abundances, especially as they change through time, do not exist. This project aims to develop a method for simultaneously measuring dynamic RNA and protein abundances through time using fluorescence microscopy. We are in the process of building the components of the system and testing the method. We intend to apply the method to perform bulked segregant analysis (BSA) quantitative trait locus (QTL) mapping experiments at the RNA and protein levels simultaneously. Ultimately we hope this method will allow us to more efficiently dissect the genetic causes of trait variation.

Current Team: Nadine Tietz, Dan Pollard

We have previously shown that an RNA interference (RNAi) pathway in the ciliate Tetrahymena thermophila plays an important role in genome integrity. In this project, we are investigating where in the genome the small RNAs (sRNAs) produced by the RNAi pathway are generated and what their potential targets might be.

Current Team: Noah Haight, Hannah Thorp, Dan Pollard, Suzanne Lee