Demonstration of transthyretin mRNA in the brain and other extrahepatic tissues in the rat

Studies were conducted to ascertain if transthyretin mRNA was present in extrahepatic tissues of the rat. A trnasthyretin cDNA clone was isolated from a lambda gt11 human liver cDNA library by antibody screening and its identity was confirmed by nucleotide sequence analysis. This transthyretin cDNA clone was used to survey poly(A+) RNA isolated from 12 different rat tissues for transthyretin mRNA by Northern blot analysis. The liver contained the highest level of transthyretin mRNA and this level was not altered by the vitamin A status of the rat. A significant amount of transthyretin mRNA was found in the brain (30% of the level of the liver) which was localized in specific regions of the brain. In addition, detectable levels of transthyretin mRNA (1% to 2% of that of the liver) were observed in the stomach, heart, skeletal muscle, and spleen. Translation of brain poly(A+) RNA in rabbit reticulocyte lysates and immunoprecipitation of the translation products with anti-transthyretin antiserum resulted in a protein band of the same size as liver pre-transthyretin. Liver pre-transthyretin was processed by the cotranslational addition of dog pancreas microsomal membranes to a protein that migrated coincidentally with monomeric serum transthyretin. These data suggest that transthyretin in the brain and the cerebrospinal fluid results from de novo synthesis and that transthyretin may play a significant physiological function, as yet unknown, within the nervous system.     

Stochastic versus augmented maximum parsimony method for estimating superimposed mutations in the divergent evolution of protein sequences. Methods tested on cytochrome c amino acid sequences.

Two ways of estimating superimposed fixed mutations in the divergent descent of proteins are examined. One method counts these in terms of a Poisson process operating within selective constraints. The other uses the maximum parsimony method to connect the contemporary sequences through intervening ancestral sequences in an evolutionary tree, and then, from the distribution of fixed mutations in dense regions of this genealogy, estimates how many fixations should be added to sparse regions. An algorithm is described which determines such augmented distances. The two methods yield similar estimates of genetic divergence when tested on a series of cytochrome c amino acid sequences. Within those constraints imposed by Darwinian selection, the dynamic behavior of the evolutionary divergence of proteins is described by the probabilistic pathways of the stochastic model. The parsimony model provides a valid Aufbau-Prinzip for examining which of those pathways occurred along a particular lineage. Concordance of the numerical magnitudes of genetic divergence estimates made by the two methods reveals them as logically consistent complements, not as mutually exclusive antagonists. Both methods indicate that cytochrome c has evolved in a non-uniform manner over geological time and more rapidly than previously estimated.