CSB Assignment Week 4

Assignments for Week 4

Note! This assignment is currently active. All significant changes will be announced on the mailing list.

 
 

Exercises for this week relate to this week's lecture.
Pre-reading for this week will prepare next week's lecture.
Exercises and pre-reading will be topics on next week's quiz.

Exercises

January 30 2014 saw the publication of what may be the most important scientific advance published in our lifetimes. In two nature papers, Haruko Obokata described the creation of so-called STAP (stimulus-triggered acquisition of pluripotency) cells. These cells can be generated by simple stress-protocols applied to leukocytes, but also to brain-, skin-, muscle-, fat-, bone marrow, lung- and liver-derived cells. Successful protocols include bathing the cells in moderately acidic medium for half an hour, mechanically perturbing the cells, or inducing plasma cell membrane pores with streptolysin. Post stress, cells shrink, stop proliferating, downregulate their differentiation gene markers and begin expressing markers of pluripotent stem cells that include our friends OCT4, Nanog, and Sox-2, and others. Cell clusters that form after this apparent transformation can be propagated. Strikingly, not only are these clusters able to grow into entire embryos after blastocyst injection, and further into normal, adult mice, but these mice are fertile and demonstrate germline transmission of their genetic markers into their offspring.

Task:
1. Read ...

Obokata et al. (2014) Stimulus-triggered fate conversion of somatic cells into pluripotency. Nature 505:641-7. (pmid: 24476887)

[ PubMed ] [ DOI ] Here we report a unique cellular reprogramming phenomenon, called stimulus-triggered acquisition of pluripotency (STAP), which requires neither nuclear transfer nor the introduction of transcription factors. In STAP, strong external stimuli such as a transient low-pH stressor reprogrammed mammalian somatic cells, resulting in the generation of pluripotent cells. Through real-time imaging of STAP cells derived from purified lymphocytes, as well as gene rearrangement analysis, we found that committed somatic cells give rise to STAP cells by reprogramming rather than selection. STAP cells showed a substantial decrease in DNA methylation in the regulatory regions of pluripotency marker genes. Blastocyst injection showed that STAP cells efficiently contribute to chimaeric embryos and to offspring via germline transmission. We also demonstrate the derivation of robustly expandable pluripotent cell lines from STAP cells. Thus, our findings indicate that epigenetic fate determination of mammalian cells can be markedly converted in a context-dependent manner by strong environmental cues.

Obvious questions arise such as:

• can these mouse-findings be transferred to humans;
• what are the upstream signals that trigger the pluripotency response; and,
• can this signalling network be controlled?

Obokata et al. describe the transformation as the release of cells from an epigenetic differentiation state, and this may point to the class of genes that could possibly be involved. How would you find them?

2. Think about what datasets you might need to pursue these questions and what comparisons you might want to undertake and what you would need to do to run these comparisons.

3. Navigate to GEO and search whether suitable datasets are available. Familiarize yourself with the query fields such as [ti] and [organism], and the boolean operators AND, OR, and NOT, (Note: capitals!).

4. Note down all datasets of interest that you find and put the links into your student Wiki page.

(Pre-)reading

Now is as good a time as any to scan two recent updates on the use of and holdings of GEO. Read briefly, we will not go over the contents in much detail but this overview may help you define how to go about task 2.

Barrett et al. (2011) NCBI GEO: archive for functional genomics data sets--10 years on. Nucleic Acids Res 39:D1005-10. (pmid: 21097893)

[ PubMed ] [ DOI ] A decade ago, the Gene Expression Omnibus (GEO) database was established at the National Center for Biotechnology Information (NCBI). The original objective of GEO was to serve as a public repository for high-throughput gene expression data generated mostly by microarray technology. However, the research community quickly applied microarrays to non-gene-expression studies, including examination of genome copy number variation and genome-wide profiling of DNA-binding proteins. Because the GEO database was designed with a flexible structure, it was possible to quickly adapt the repository to store these data types. More recently, as the microarray community switches to next-generation sequencing technologies, GEO has again adapted to host these data sets. Today, GEO stores over 20,000 microarray- and sequence-based functional genomics studies, and continues to handle the majority of direct high-throughput data submissions from the research community. Multiple mechanisms are provided to help users effectively search, browse, download and visualize the data at the level of individual genes or entire studies. This paper describes recent database enhancements, including new search and data representation tools, as well as a brief review of how the community uses GEO data. GEO is freely accessible at http://www.ncbi.nlm.nih.gov/geo/.

Barrett et al. (2013) NCBI GEO: archive for functional genomics data sets--update. Nucleic Acids Res 41:D991-5. (pmid: 23193258)

[ PubMed ] [ DOI ] The Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) is an international public repository for high-throughput microarray and next-generation sequence functional genomic data sets submitted by the research community. The resource supports archiving of raw data, processed data and metadata which are indexed, cross-linked and searchable. All data are freely available for download in a variety of formats. GEO also provides several web-based tools and strategies to assist users to query, analyse and visualize data. This article reports current status and recent database developments, including the release of GEO2R, an R-based web application that helps users analyse GEO data.