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Biomedical subjects

Louise J Johnson

Publications and source records attributed to Louise J Johnson.

2 recordsLinked to original sources

Population genetics of the wild yeast Saccharomyces paradoxus.

Saccharomyces paradoxus is the closest known relative of the well-known S. cerevisiae and an attractive model organism for population genetic and genomic studies. Here we characterize a set of 28 wild isolates from a 10-km(2) sampling area in southern England. All 28 isolates are homothallic (capable of mating-type switching) and wild type with respect to nutrient requirements. Nine wild isolates and two lab strains of S. paradoxus were surveyed for sequence variation at six loci totaling 7 kb, and all 28 wild isolates were then genotyped at seven polymorphic loci. These data were used to calculate nucleotide diversity and number of segregating sites in S. paradoxus and to investigate geographic differentiation, population structure, and linkage disequilibrium. Synonymous site diversity is approximately 0.3%. Extensive incompatibilities between gene genealogies indicate frequent recombination between unlinked loci, but there is no evidence of recombination within genes. Some localized clonal growth is apparent. The frequency of outcrossing relative to inbreeding is estimated at 1.1% on the basis of heterozygosity. Thus, all three modes of reproduction known in the lab (clonal replication, inbreeding, and outcrossing) have been important in molding genetic variation in this species.

Base Sequence↗

Evolution of spatial expression pattern.

How can complex patterns of gene expression evolve? Understanding the near-precise repeatability of morphology created by animal development, through the interactions between morphogens and networks of transcription factors, is one of the most difficult outstanding problems in developmental biology. Spatial patterns are created in part by interactions between transcription factors and their DNA targets. Here we simulate the evolution of such interactions to compare the success and the evolvability of simple and complex gene networks in reaching a desired spatial pattern of expression along an embryo. We find that adding more genes to a network makes only a slight difference to evolvability. Expression patterns can evolve within a few hundred mutational events, and some simulations show partial redundancy. However, there is wide variation between simulations, with both simple and complex networks being liable to reach evolutionary "dead ends" that can only be escaped by means of an advantageous combination of individually deleterious mutations.

Biological Evolution↗