Week 4: St. Patrick's Donuts, Sorting, Statistics, and Some More DEG Analysis!

Hi everyone! I hope everyone enjoyed their March Break—or maybe tried out some of Krispy Kreme’s St. Patrick’s-themed donuts (I certainly did, and they were delicious). This week, I only went to the lab for two days as I was mostly focused on coding, coding, and more coding!

On Friday, I attended the Wagner Lab meeting, where I heard a grad student’s amazing work on understanding molecular mechanisms during canalization in zebrafish embryo development, including how hypoxia and anoxia affect signaling pathways during development. 

We also planned that day our experiment aimed to induce oogenesis in culture by isolating germ and somatic cells from the gonads of our embryos — the reconstituted embryonic mouse ovaries (rOvaries). Once again, that called for — you guessed it — a dissection! After dissecting the pregnant mouse to find her embryos, it turns out it’s really hard to find developing gonads from those mouse embryos! Luckily, my advisor was there to help me throughout the process and help me retrieve the gonads! We gathered our controls and our ovaries. After more dissociation/preparing for the sort steps, we went down to the sorter, but as it turns out, we did not have enough oogonia for the main experiment 🙁 We cannot bank oogonia and keep collecting over time until we have enough — they must be used fresh. This presents several problems as it means we have to hope that every time we check in on our mouse at the timepoint we want to test, she is a) pregnant, b) has enough embryos, c) has enough female embryos, and d) the ovaries from the embryos have enough oogonia. We are currently troubleshooting to find out ways to optimize the retrieval of the oogonia for better yield!

Tuesday, we repeated the sort, but this time, we dissected a mouse from a different mouse line as this was for another lineage tracing experiment (more on what that is next week) my advisor has been working on. I also took some time to practice my microscope dissection skills by trying to retrieve the gonads of the male embryos alone. After taking a very long time and nearly shredding the tiny sample, I was able to finally find the testes out of the 2 male embryos I was dissecting!! (There are a pair of testes in each embryo, so I was only able to find half the gonads, but still — progress!). We prepared for the sort, went down to the sorting machine again, and got the germ and somatic cells we needed.

On the computational side, since last time, I’ve been learning about and using differential gene expression analysis, specifically using the pyDESeq2 package and using the Wilcoxon Rank Sum statistical test to analyze more RNA-seq datasets. More recently, I’ve been using Gene Set Enrichment Analysis (GSEA) to check whether the differentially expressed genes can be found in pathways in already annotated gene sets — essentially, whether the genes are positively or negatively enriched among the gene sets. This shows genes that are likely being modulated at the time point we are performing the GSEA analysis.

Since I didn’t show it in Week 2, here is an example of some differential gene expression testing (using pyDESeq2 and another statistcal test called wilcoxon!) The first image does a comparison of all anterior vs posterior PGCs while the second image does a timepoint comparison of the PGCs.