Month: November 2017

We started the week discussing gene regulation – how cellular systems regulate the amounts of protein products (RNA, protein). The famous lac operon system was introduced; this set of genes in E. coli provided the foundation for much of our understanding of regulation at the transcriptional level. We then turned to discuss the similar gal system in yeast as a model for eukaryotes before considering some post-transcriptional forms of regulation such as alternative splicing and RNAi. On Thursday we turned to population and evolutionary genetics. Much of the discussion centered on the Hardy-Weinberg Principle of population genetics which provides important avenues for calculating genotype frequencies and allele frequencies. The class discussed some of the key underlying assumptions of the H-W Principle as well as two major implications of that principle for population genetic processes. Lecture material transitioned to a bit about evolutionary genetics with special emphasis on the forces of evolution. Mutation, although the most fundamental of the forces that provides the key ‘variation substrate’ for other evolutionary forces to act upon, is also a very weak evolutionary force because it is not able to cause rapid change in allele frequencies (unless population sizes are very, very small). Genetic drift was also discussed – the role of ‘sampling error’ of gametes from one generation to the next. When population sizes are small, there is a high probability that one particular allele might be completely lost (or completely fixed) in the population simply because that allele happened not to be ‘sampled’ purely due to chance from one generation to the next. An analogy used to help make drift more understandable is flipping a coin – with one million coin flips, you are very likely to end up with something very close to 50% heads and 50% tails (and almost certainly heads and tails getting sampled at least once) whereas with a much smaller number of coin flips (six, for example) there is a much greater chance of not getting a ‘50/50’ result and not either getting heads or tails at all in the series of coin flips.

We also discussed Muller’s Ratchet – a theoretical evolutionary concept not covered in the book. The idea behind the ratchet is that if you have a small isolated population that reproduces asexually, you might expect to lose the most-fit class of individual in that population (individual with fewest deleterious alleles) by drift. On top of this, because the population is small, mutation is a stronger force – individuals are accumulating new deleterious mutations on top of this. With no input of genetic variation from migration and no recombination, such populations would be expected to over time become less and less fit (individuals harboring increasing numbers of deleterious alleles) until it reaches extinction. How optimistic! This might seem rather unrealistic, but the theory has served as a model for helping evolutionary geneticists understand why other evolutionary forces (such as recombination) came about. Also, there are some asexual genetic components of endangered populations (e.g., mitochondrial DNA) that might be subject to the ratchet. Why ‘ratchet’? The idea here is that every time the population gets worse (loses most-fit individual) due to drift, this is a turn of the ratchet toward extinction.

Week 9 Sneak Peek: We will finish up Thursday’s lecture material, and then continue our population/evolutionary-genetic unit by discussing natural selection – Darwin’s key premises and deduction leading to his theory, and the many different sub-types of selection that are possible. We will focus on one test for the effects of natural selection on protein-coding sequences. I will also be posting some supplemental reading on this topic – it is a primary research article that I will be covering. Reading this paper is not absolutely required, but might help you understand things a bit better. Remember: no class on Thursday, and no recitation all week!

This week we wrapped up a little bit of recombination, then turned our focus toward mutation and then cancer genetics.  We turned attention to the molecular mechanisms of DNA recombination, overviewing a few early (but ultimately incorrect) models before learning about the double-stranded (ds)DNA break pathway, which is currently held as the correct model.  dsDNA break-mediated recombination can give rise to both recombinant as well as non-recombination chromosomes depending on how chi structures are resolved, and can also result in gene conversion events.  The example of yeast mating-type switching provided an example of dsDNA break-mediated recombination occurring between repetitive DNA sequences on the same molecule (between hidden and silenced ‘mating cassettes’ and the expressed MAT gene itself).

Next, we first learned about different pathways by which DNA can mutate, ranging from base substitution changes resulting from the natural fluctuations in electron distributions in nucleotides (for example, the keto versus enol form example in thymine) to the significant genome alterations that can result from mobile genetic elements such as retrotransposons. We also learned about how mutations can be classified in a variety of ways.  Our discussion of mutation concluded with the topic of mutation rates, covering two different methods for how such rates can be experimentally estimated (reporter gene versus mutation-accumulation line approach). Reporter gene approaches rely on the phenotypes associated known to occur when the gene is mutated. The phenotypic change (for example, from blue to white colony of E. coli cells) reports the occurrence of a mutation. With mutation-accumulation lines, on the other hand, organisms are propagated across many (usually hundreds) of generations in the lab, and then their DNA is directly sequenced afterwards to count mutations at the DNA-level. This strategy offers a much more direct avenue (not relying on assumptions about reporter gene phenotypes) to understanding the mutation process. On Thursday, our attention turned toward cancer genetics. This lecture also highlighted the utility of temperature-sensitive mutants in genetic analysis with the yeast model organism. We learned about how cyclin-CDK complexes regulate cell cycle progression.

Week 7 Sneak Peek: We will wrap up cancer genetics on Tuesday, and transition to some basic discussion about gene expression (for example, transcription basics). Thursday will be midterm #2… Study hard! Bring your calculators! The basic format will be the same as the first midterm – about 45% of the points coming from multiple choice and about 55% coming from short answer. This exam will cover all material up through (and including) next Tuesday’s lecture content. Material covered in-between Midterm #1 and #2 will be the main emphasis of the questions, though you will still need the knowledge base of material presented early in the class to succeed. Also, reminder that next week on Friday is Veteran’s Day, and OSU will not be in session.