Extent of genomic rearrangement after genome duplication in yeast

Whole-genome duplication approximately 108 years ago was proposed as an explanation for the many duplicated chromosomal regions in Saccharomyces cerevisiae. Here we have used computer simulations and analytic methods to estimate some parameters describing the evolution of the yeast genome after this duplication event. Computer simulation of a model in which 8% of the original genes were retained in duplicate after genome duplication, and 70–100 reciprocal translocations occurred between chromosomes, produced arrangements of duplicated chromosomal regions very similar to the map of real duplications in yeast. An analytical method produced an independent estimate of 84 map disruptions. These results imply that many smaller duplicated chromosomal regions exist in the yeast genome in addition to the 55 originally reported. We also examined the possibility of determining the original order of chromosomal blocks in the ancestral unduplicated genome, but this cannot be done without information from one or more additional species. If the genome sequence of one other species (such as Kluyveromyces lactis) were known it should be possible to identify 150–200 paired regions covering the whole yeast genome and to reconstruct approximately two-thirds of the original order of blocks of genes in yeast. Rates of interchromosome translocation in yeast and mammals appear similar despite their very different rates of homologous recombination per kilobase.

The optimization principle in phylogenetic analysis tends to give incorrect topologies when the number of nucleotides or amino acids used is small

In the maximum parsimony (MP) and minimum evolution (ME) methods of phylogenetic inference, evolutionary trees are constructed by searching for the topology that shows the minimum number of mutational changes required (M) and the smallest sum of branch lengths (S), respectively, whereas in the maximum likelihood (ML) method the topology showing the highest maximum likelihood (A) of observing a given data set is chosen. However, the theoretical basis of the optimization principle remains unclear. We therefore examined the relationships of M, S, and A for the MP, ME, and ML trees with those for the true tree by using computer simulation. The results show that M and S are generally greater for the true tree than for the MP and ME trees when the number of nucleotides examined (n) is relatively small, whereas A is generally lower for the true tree than for the ML tree. This finding indicates that the optimization principle tends to give incorrect topologies when n is small. To deal with this disturbing property of the optimization principle, we suggest that more attention should be given to testing the statistical reliability of an estimated tree rather than to finding the optimal tree with excessive efforts. When a reliability test is conducted, simplified MP, ME, and ML algorithms such as the neighbor-joining method generally give conclusions about phylogenetic inference very similar to those obtained by the more extensive tree search algorithms.

Neuronal type information encoded in the basic-helix–loop–helix domain of proneural genes

The proneural genes encode basic-helix–loop–helix (bHLH) proteins and promote the formation of distinct types of sensory organs. In Drosophila, two sets of proneural genes, atonal (ato) and members of the achaete–scute complex (ASC), are required for the formation of chordotonal (ch) organs and external sensory (es) organs, respectively. We assayed the production of sensory organs in transgenic flies expressing chimeric genes of ato and scute (sc), a member of ASC, and found that the information that specifies ch organs resides in the bHLH domain of ato; chimeras containing the b domain of ato and the HLH domain of sc also induced ch organ formation, but to a lesser extent than those containing the bHLH domain of ato. The b domains of ato and sc differ in seven residues. Mutations of these seven residues in the b domain of ato suggest that most or perhaps all of these residues are required for induction of ch organs. None of these seven residues is predicted to contact DNA directly by computer simulation using the structure of the myogenic factor MyoD as a model, implying that interaction of ato with other cofactors is likely to be involved in neuronal type specification.