Slide 1The Genetic CodeSlide 3Slide 4Why the canonical code?The Polar RequirementHow Optimal is the Canonical Code?One in a million?Slide 9Slide 10Beyond the Polar RequirementSlide 12Slide 13Other optimizations…Is the canonical code optimized?Slide 16Benjamin GoodBenjamin GoodMarch 17, 2008March 17, 2008The Genetic Code•Sequence constructed from 4 “letters” known as nucleotides or bases, denoted “A”, “G”, “C”, “U” / ”T”•These letters form fixed length “words” known as codons.•Groups of codons form “sentences” which encode proteins. CodonThe Genetic Code•A given codon can either stand for a specific amino acid or act as a “start/stop codon”, which signals either the beginning or end of a protein’s code respectively.•There are 4*4*4=64 different codons but only 20 amino acids to code for, making a total of 21 different possible meanings for a given codon (including start/stop).•How are codons distributed among the 21 different categories?The Genetic Code•The “Canonical Code”•But why this arrangement and not another?•Crick: Canonical code is a frozen artifact of a code that was “good enough” to workWhy the canonical code?•An alternative is that the canonical code itself evolved to optimize for some selected trait.•Noting the connection between similar codons and similar amino acids, several researchers hypothesized that the canonical code evolved to optimize against copying/transcription errors.The Polar Requirement•Woese and Alf-Steinberger came up with a measure for error susceptibility in genetic code based on hydrophobicity.•A given codon is subject to a single mutation. The polar difference between the new amino acid and the old one is calculated. •The “error” resulting from the mutation is taken as the distance squared (mean squared distance).How Optimal is the Canonical Code?•Unfortunately, Alf-Steinberger’s results have not been reproducible. •The first reproducible “test” of the polar requirement was published by Haig and Hurst in 1991.•Using this method, they calculated the total error for a large sample of possible code assignments.•Out of 10,000, only twoother codes had lowererror values than thecanonical code!One in a million?•Freeland and Hurst built upon H&H’s model to introduce more realistic assumptions.•Two types of code errors possible: transition andtransversion.•Introduced weighting fortwo types of errors because they are not equally probable in nature.•Also introduced bias towardsmistranslation rather thanmutation (higher rates oferrors in 1st and 3rd slots)One in a million?Weighted errors make the canonicalcode even more optimized relativeto the rest.Peak efficiencyAround w = 3One in a million?Out of a sampleof 1,000,000random codes,only 1 had a lower error valuethan the CC!It was relativelyfar away in search space,but behavedsimilarly to CC.Beyond the Polar Requirement•In the paper we read for class, Freeland and Hurst question previous studies (including their own).•Is the polar requirement a biased measurement?•Is using the (W)MSD a biased measurement?•Some biosynthetic acids might be tied to particular codons, so code space could be artificially symmetric.Proposed a new measurement based on PAM matrices, which measure the “similarity” of two amino acids on a functional level.Beyond the Polar RequirementGeneral error metric:A code’s total error =αi is the number oftransition errors leadingto substitution i.i.e. U ↔ C,A↔Gβi is the number oftransversion errors leadingto substitution i.i.e. U,C ↔ A,Gei is the physical error resulting from substitution iPolar requirementPAM matrixBeyond the Polar Requirement•Results:PAM MatrixPolar RequirementFar from overturning the adaptive hypothesis, this new study showed thecanonical code to be even more optimized than previously thought!Other optimizations…•Studies of the assignment of stop codons found that the canonical code is highly optimized against frameshift and nonsense mutations. (S. Naumenko et al., 2008)•Furthermore, these same optimizations against frame shift errors allow the CC to be more efficient at encoding parallel information on top of a protein coding sequence. (Itzkovitz and Alon, 2007)Is the canonical code optimized?•YES!•But many aspects are still unclear – e.g. a mechanism for code selection.•Conditions in precanonical times are still relatively unknown and the canonical code seems to be universally adhered to in modern
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