A large-scale screen for artificial selection in maize identifies candidate agronomic loci for domestication and crop improvement

Molecular and functional diversity of maize

Over the past 10,000 years, man has used the rich genetic diversity of the maize genome as the raw material for domestication and subsequent crop improvement. Recent research efforts have made tremendous strides toward characterizing this diversity: structural diversity appears to be largely mediated by helitron transposable elements, patterns of diversity are yielding insights into the number and type of genes involved in maize domestication and improvement, and functional diversity experiments are leading to allele mining for future crop improvement. The development of genome sequence and germplasm resources are likely to further accelerate this progress.

Variation in mutation dynamics across the maize genome as a function of regional and flanking base composition

We examine variation in mutation dynamics across a single genome (Zea mays ssp. mays) in relation to regional and flanking base composition using a data set of 10,472 SNPs generated by resequencing 1776 transcribed regions. We report several relationships between flanking base composition and mutation pattern. The A + T content of the two sites immediately flanking the mutation site is correlated with rate, transition bias, and GC --> AT pressure. We also observe a significant CpG effect, or increase in transition rate at CpG sites. At the regional level we find that the strength of the CpG effect is correlated with regional A + T content, ranging from a 1.7-fold increase in transition rate in relatively G + C-rich regions to a 2.6-fold increase in A + T-rich regions. We also observe a relationship between locus A + T content and GC --> AT pressure. This regional effect is in opposition to the influence of the two immediate neighbors in that GC --> AT pressure increases with increasing locus A + T content but decreases with increasing flanking base A + T content and may represent a relationship between genome location and mutation bias. The data indicate multiple context effects on mutations, resulting in significant variation in mutation dynamics across the genome.