Laura L. Mays Hoopes

The yeast Sgs1 helicase is differentially required for genomic and ribosomal DNA replication

The members of the RecQ family of DNA helicases play conserved roles in the preservation of genome integrity. RecQ helicases are implicated in Bloom and Werner syndromes, which are associated with genomic instability and predisposition to cancers. The human BLM and WRN helicases are required for normal S phase progression. In contrast, Saccharomyces cerevisiae cells deleted for SGS1 grow with wild‐type kinetics. To investigate the role of Sgs1p in DNA replication, we have monitored S phase progression in sgs1Δ cells. Unexpectedly, we find that these cells progress faster through S phase than their wild‐type counterparts. Using bromodeoxyuridine incorporation and DNA combing, we show that replication forks are moving more rapidly in the absence of the Sgs1 helicase. However, completion of DNA replication is strongly retarded at the rDNA array of sgs1Δ cells, presumably because of their inability to prevent recombination at stalled forks, which are very abundant at this locus. These data suggest that Sgs1p is not required for processive DNA synthesis but prevents genomic instability by coordinating replication and recombination events during S phase.

The Genomics Education Partnership: Successful Integration of Research into Laboratory Classes at a Diverse Group of Undergraduate Institutions

Genomics is not only essential for students to understand biology but also provides unprecedented opportunities for undergraduate research. The goal of the Genomics Education Partnership (GEP), a collaboration between a growing number of colleges and universities around the country and the Department of Biology and Genome Center of Washington University in St. Louis, is to provide such research opportunities. Using a versatile curriculum that has been adapted to many different class settings, GEP undergraduates undertake projects to bring draft-quality genomic sequence up to high quality and/or participate in the annotation of these sequences. GEP undergraduates have improved more than 2 million bases of draft genomic sequence from several species of Drosophila and have produced hundreds of gene models using evidence-based manual annotation. Students appreciate their ability to make a contribution to ongoing research, and report increased independence and a more active learning approach after participation in GEP projects. They show knowledge gains on pre- and postcourse quizzes about genes and genomes and in bioinformatic analysis. Participating faculty also report professional gains, increased access to genomics-related technology, and an overall positive experience. We have found that using a genomics research project as the core of a laboratory course is rewarding for both faculty and students.

A Course-Based Research Experience: How Benefits Change with Increased Investment in Instructional Time

While course-based research in genomics can generate both knowledge gains and a greater appreciation for how science is done, a significant investment of course time is required to enable students to show gains commensurate to a summer research experience. Nonetheless, this is a very cost-effective way to reach larger numbers of students.

Nucleic Acid Blotting: Southern and Northern

E.M. Southern invented blotting of DNA in 1975; the method was extended to RNA in 1977. Standard Southern blotting includes limited depurination, denaturation, and neutralization of the DNA in gels (where they have been separated in size by electrophoresis) and capillary transfer of the DNA onto nitrocellulose or nylon blotting membranes. For northern blotting, RNA is guarded from base and RNase, denatured, separated by electrophoresis, and then blotted to nylon blotting membranes. Both types of blots are then blocked to prevent nonspecific binding, hybridized with probe, and washed. Next the sequences of interest are located by detecting labeled probes. Alternative methods involve dot/slot blotting when the size of the nucleic acid being probed is not of interest. Electrophoretic transfer from polyacrylamide gels can be used when the nucleic acid fragments of interest are too small to be effectively resolved on agarose gels. Artifacts in Southern blot can result from incomplete digestion, overloading the blotting membrane, incomplete blocking, damaged blot media, and air bubbles. In northern blotting, RNA quality must be monitored, and RNA that is degraded or contaminated with excess DNA should be avoided.

Marianne Bronner-Fraser

Note from the Editor Educator Highlights for CBE—Life Sciences Education show how professors at different kinds of institutions educate students in life sciences with inspiration and panache. If you have a particularly creative teaching portfolio yourself, or if you wish to nominate an inspiring colleague to be profiled, please e-mail Laura Hoopes at lhoopes@pomona.edu.

H. Craig Heller

Note from the Editor Educator Highlights for CBE—Life Sciences Education show how professors at different kinds of institutions educate students in life sciences with inspiration and panache. If you have a particularly creative teaching portfolio yourself, or if you wish to nominate an inspiring colleague to be profiled, please e-mail Laura Hoopes at ude.anomop@sepoohl.

Yeast through the Ages: a Statistical Analysis of Genetic Changes in Aging Yeast

Microarray technology allows for the expression levels of thousands of genes in a cell to be measured simultaneously. The technology provides great potential in the fields of biology and medicine as the analysis of data obtained from microarray experiments gives insight into the roles of specific genes and the associated changes across experimental conditions (e.g., aging, mutation, radiation therapy, drug dosage, ...). The application of statistical tools to microarray data can help make sense of the experiment and thereby advance genetic, biological, and medical research. Likewise, microarrays provide an exciting means through which to explore different statistical techniques. Our paper focuses on the analysis of data from a yeast DNA microarray experiment. The biological question that motivates our research is “What genetic changes in yeast happen over time?” In order to explore the research question of interest we first standardize the data to correct for errors that arise in the data due to biases from the complex microarray procedure. Once we have data that accurately depicts the natural variability in the genes and arrays (as opposed to variability due to technical aspects of the microarray chip), we can focus on our primary interest: the analysis of yeast gene expression to further uncover the quantitative relationship between the gene expression levels and the generation (age) of the yeast cell. We use a statistical tool called predication analysis for microarrays (PAM) [3]; PAM is a classification tool that provides insight into different groupings of the generations of yeast. PAM isolates and identifies specific genes using a threshold value and creates a model to predict the generation for an independent sample array. We also attempt to improve the results obtained from PAM by using t-tests to pre-filter genes before introducing them into the PAM model.