Week 1 HW: Principles and Practices

1. Describe a biological engineering application or tool you want to develop and why: I want to develop a diagnostics chip for neuropsychiatric disorders (microarray or microfluidics based). 2. Describe one or more governance/policy goals related to ensuring that this application or tool contributes to an “ethical” future Policy goals would prevent misuse of diagnostics for measurement of features like “intelligence” or personality traits. Policies would need to limit interpretable results to areas of high variability in specific diseases and include diverse populations. 3. Three Governance Actions One: Federal oversight of use of genetic data. Prevention of use of data for non-psychiatric disease related traits.
Two: Standardized, valid production of chips. Quality control. Three: Ensuring equal genetic information from diverse ancestries for diagnostics.

At this moment in time, I would prioritize option three. Without adequate information of diseases in diverse populations the diagnostic tool would have limited use in populations.

Slide questions: Jacobsen: Error rate: 1x10^6 Given the rate and length of genome (3.2billion base pairs) rate of error would be 3200 errors per DNA replication. This is addressed through various DNA repair pathways in the cell.

There are 10^623 ways to code for the average protein. The number of possibilities is dramatically reduced to the 3D conformational constraints and stability of the sequence.

Leproust: Most commonly used method: phosphoramidite method Difficult to sequences longer than 200bp because: Yield greatly decreases after 200bp with traditional methods. 2000bp gene cannot be made because: Current limits for oligonucleotides are much shorter.

Church: The ten essential amino acids are histidine, isoleucine, leucine, lysine, methionine, phenylalanine, threonine, tryptophan, valine. Oddly, this validates the “lysine contingency” as the dinosaurs are indeed dependent on this essential amino acid.