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Genetics Lecture No. 19.docx

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Department
Biology
Course
Biology 2581B
Professor
Jim Karagiannis
Semester
Spring

Description
Genetics Lecture No. 19: Functional Genomics & Systems Biology th Wednesday March 20 , 2013 Landmarks In The History Of Genetics & The Genomic Eras: -One of the most recent landmarks in the history of genetics was providing an answer to the question of how information in a genome is expressed to produce a living organism through the results of the Human Genome Project. These results forever divided the realm of genetic studies into pre-genomic era (before the HGP) and a post-genomic era (after the HGP). In the pre-genomic era, researchers engaged in forward genetics and focused on the relationship between phenotype and genotype (e.g. discovering the genetic basis for cystic fibrosis). In the post-genomic era, researchers engage in both forward and reverse genetics, focused on the relationship between genome and phenome. For example, in cancer, many genes are involved in the control of cellular proliferation (cancer is a multi-step process with multiple genes and pathways involved). This understanding of cancer shows that the relationship between genotype and phenotype is not so simple as cancer arises due to the defects in the dynamic interaction of many components. Reductionism Vs. The Systems-Oriented Approach; -Reductionism is seen as an old notion in genetics that states the behaviour of a biological system can be explained by the properties of its constituent parts. A more integrative approach is the idea of systems biology, where biological systems exhibit “emergent” properties that are possessed by the system as a whole, and not by any isolated part of that system. Where reductionism sees the singling out of one factor sufficient for experimental study, the systems- oriented approach requires there be many factors simultaneously evaluated in order to assess the dynamics of the system. In certain cases, reductionism becomes an optimal approach when one or a few components are responsible for the overall behaviour of the system (e.g. CF). But when interactions between components are responsible for the overall behaviour of a system (e.g. cancer), it is best to the systems-oriented approach as the basis for understanding. The Systems-Oriented Approach: -Systems biology is explores biological phenomena using large-scale technologies to generate data and computational tools to analyze the data. The systems-oriented approach is an important process in systems biology that starts with identifying the numerous parts of the biological system (e.g. proteins, genes, metabolites, cells, tissues, and organs). Then we must determine the roles each of these elements possesses in that biological system (e.g. function, regulation), and how exactly these components dynamically interact to give rise to the system’s emergent properties (traits or behaviours that arise from the operation of a biological system as a whole). In summary, in the traditional approach, there is a definitive relationship between genotype and phenotype of wild-type and mutant alleles, whereas in the systems-oriented approach, the behaviour of the network as a whole (mutant vs. wild-type networks as opposed to a single gene) is the primary focus. Roles Of The Individual Parts & The Dynamic Nature Of The Lac Operon: -The Lac operon is a stretch of DNA sequence found in E. coli containing many components that are collectively responsible for the metabolism of lactose: β-Galactosidease breaks down lactose, Lactose permease imports lactose into the cell, LacI repressor protein represses transcription of the lac operon, operator is where the repressor binds, allolactose allosterically regulates the repressor, CRP activates transcription of the lac operon, cAMP allosterically regulates CRP by binding to the CRP binding site to form CRP-cAMP complex, and glucose reduces cAMP levels present. Within the regulation and function of the Lac operon, there is inherent dynamic interaction that contributes to lactose metabolism. Many protein-DNA interactions (e.g. repressor binding operator, CRP/cAMP binding promoter), allosteric interactions (e.g. allolactose binding repressor protein, cAMP binding CRP) are present in both the positive layer of regulation (glucose, cAMP, CRP) and the negative layer of regulation (allolactose LacI repressor) in transcription of the Lac operon. The Binary Logical Circuit: -If you look at the interactions concerning the Lac operon, as a “logic gate,” you can define the behaviour of the system as a logical AND gate since you only get high expression when you have allolactose and cAMP present (shown in the graph with [cAMP] on the x-axis and [allolactose] on the y-axis). By measuring [cAMP] and [allolactose] and graphing that data along with the level of lacZ transcription (dark red = high expression, dark blue = low expression), you can see the behaviour of the system closely resembled in this theoretical graph. Essentially, a binary logical circuit “emerges” from this set of interacting parts. The behaviour of the system (effect on Lac operon regulation) can be altered through random mutations in the cis-acting elements of the Lac promoter, where the system is converted from an AND gate to an OR gate (high expression when allolactose or cAMP are present). In summary, if you didn’t understand this emergent property (AND gate), you wouldn’t be able to properly understand the behaviour of the system (e.g. getting lost in the biochemical details of the Lac operon). Note however that this emergent property is selectable by evolution and the beh
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