Forward and reverse genetics of rapid-cycling Brassica oleracea.

Seeds of rapid-cycling Brassica oleracea were mutagenized with the chemical mutagen, ethylmethane sulfonate. The reverse genetics technique, TILLING, was used on a sample population of 1,000 plants, to determine the mutation profile. The spectrum and frequency of mutations induced by ethylmethane sulfonate was similar to that seen in other diploid species such as Arabidopsis thaliana. These data indicate that the mutagenesis was effective and demonstrate that TILLING represents an efficient reverse genetic technique in B. oleracea that will become more valuable as increasing genomic sequence data become available for this species. The extensive duplication in the B. oleracea genome is believed to result in the genetic redundancy that has been important for the evolution of morphological diversity seen in today's B. oleracea crops (broccoli, Brussels sprouts, cauliflower, cabbage, kale and kohlrabi). However, our forward genetic screens identified 120 mutants in which some aspect of development was affected. Some of these lines have been characterized genetically and in the majority of these, the mutant trait segregates as a recessive allele affecting a single locus. One dominant mutation (curly leaves) and one semi-dominant mutation (dwarf-like) were also identified. Allelism tests of two groups of mutants (glossy and dwarf) revealed that for some loci, multiple independent alleles have been identified. These data indicate that, despite genetic redundancy, mutation of many individual loci in B. oleracea results in distinct phenotypes.

Retrotransposons Are the Major Contributors to the Expansion of the Drosophila ananassae Muller F Element.

The discordance between genome size and the complexity of eukaryotes can partly be attributed to differences in repeat density. The Muller F element (∼5.2 Mb) is the smallest chromosome in Drosophila melanogaster, but it is substantially larger (>18.7 Mb) in D. ananassae To identify the major contributors to the expansion of the F element and to assess their impact, we improved the genome sequence and annotated the genes in a 1.4-Mb region of the D. ananassae F element, and a 1.7-Mb region from the D element for comparison. We find that transposons (particularly LTR and LINE retrotransposons) are major contributors to this expansion (78.6%), while Wolbachia sequences integrated into the D. ananassae genome are minor contributors (0.02%). Both D. melanogaster and D. ananassae F-element genes exhibit distinct characteristics compared to D-element genes (e.g., larger coding spans, larger introns, more coding exons, and lower codon bias), but these differences are exaggerated in D. ananassae Compared to D. melanogaster, the codon bias observed in D. ananassae F-element genes can primarily be attributed to mutational biases instead of selection. The 5' ends of F-element genes in both species are enriched in dimethylation of lysine 4 on histone 3 (H3K4me2), while the coding spans are enriched in H3K9me2. Despite differences in repeat density and gene characteristics, D. ananassae F-element genes show a similar range of expression levels compared to genes in euchromatic domains. This study improves our understanding of how transposons can affect genome size and how genes can function within highly repetitive domains.

A study assessing the potential of negative effects in interdisciplinary math-biology instruction.

There is increasing enthusiasm for teaching approaches that combine mathematics and biology. The call for integrating more quantitative work in biology education has led to new teaching tools that improve quantitative skills. Little is known, however, about whether increasing interdisciplinary work can lead to adverse effects, such as the development of broader but shallower skills or the possibility that math anxiety causes some students to disengage in the classroom, or, paradoxically, to focus so much on the mathematics that they lose sight of its application for the biological concepts in the center of the unit at hand. We have developed and assessed an integrative learning module and found disciplinary learning gains to be equally strong in first-year students who actively engaged in embedded quantitative calculations as in those students who were merely presented with quantitative data in the context of interpreting biological and biostatistical results. When presented to advanced biology students, our quantitative learning tool increased test performance significantly. We conclude from our study that the addition of mathematical calculations to the first year and advanced biology curricula did not hinder overall student learning, and may increase disciplinary learning and data interpretation skills in advanced students.

Introduction to the statistical analysis of two-color microarray data.

Microarray experiments have become routine in the past few years in many fields of biology. Analysis of array hybridizations is often performed with the help of commercial software programs, which produce gene lists, graphs, and sometimes provide values for the statistical significance of the results. Exactly what is computed by many of the available programs is often not easy to reconstruct or may even be impossible to know for the end user. It is therefore not surprising that many biology students and some researchers using microarray data do not fully understand the nature of the underlying statistics used to arrive at the results.We have developed a module that we have used successfully in undergraduate biology and statistics education that allows students to get a better understanding of both the basic biological and statistical theory needed to comprehend primary microarray data. The module is intended for the undergraduate level but may be useful to anyone who is new to the field of microarray biology. Additional course material that was developed for classroom use can be found at http://www.polyploidy.org/ .In our undergraduate classrooms we encourage students to manipulate microarray data using Microsoft Excel to reinforce some of the concepts they learn. We have included instructions for some of these manipulations throughout this chapter (see the "Do this..." boxes). However, it should be noted that while Excel can effectively analyze our small sample data set, more specialized software would typically be used to analyze full microarray data sets. Nevertheless, we believe that manipulating a small data set with Excel can provide insights into the workings of more advanced analysis software.

Integration of flowering signals in winter-annual Arabidopsis.

Photoperiod is the primary environmental factor affecting flowering time in rapid-cycling accessions of Arabidopsis (Arabidopsis thaliana). Winter-annual Arabidopsis, in contrast, have both a photoperiod and a vernalization requirement for rapid flowering. In winter annuals, high levels of the floral inhibitor FLC (FLOWERING LOCUS C) suppress flowering prior to vernalization. FLC acts to delay flowering, in part, by suppressing expression of the floral promoter SOC1 (SUPPRESSOR OF OVEREXPRESSION OF CONSTANS1). Vernalization leads to a permanent epigenetic suppression of FLC. To investigate how winter-annual accessions integrate signals from the photoperiod and vernalization pathways, we have examined activation-tagged alleles of FT and the FT homolog, TSF (TWIN SISTER OF FT), in a winter-annual background. Activation of FT or TSF strongly suppresses the FLC-mediated late-flowering phenotype of winter annuals; however, FT and TSF overexpression does not affect FLC mRNA levels. Rather, FT and TSF bypass the block to flowering created by FLC by activating SOC1 expression. We have also found that FLC acts as a dosage-dependent inhibitor of FT expression. Thus, the integration of flowering signals from the photoperiod and vernalization pathways occurs, at least in part, through the regulation of FT, TSF, and SOC1.