AI Article Synopsis

  • Improved predictions of fitness and yield can be achieved by understanding the genetics and environmental influences on the growth of organisms.
  • Researchers studied leaf lengths and widths in Brassica rapa and modeled growth as function-valued traits (FVT) to uncover genetic links to various biological aspects.
  • They discovered unique genetic relationships between leaf shape (allometry) and other traits, suggesting that optimizing leaf shape could enhance crop performance without harming other important characteristics.

Article Abstract

Improved predictions of fitness and yield may be obtained by characterizing the genetic controls and environmental dependencies of organismal ontogeny. Elucidating the shape of growth curves may reveal novel genetic controls that single-time-point (STP) analyses do not because, in theory, infinite numbers of growth curves can result in the same final measurement. We measured leaf lengths and widths in Brassica rapa recombinant inbred lines (RILs) throughout ontogeny. We modeled leaf growth and allometry as function valued traits (FVT), and examined genetic correlations between these traits and aspects of phenology, physiology, circadian rhythms and fitness. We used RNA-seq to construct a SNP linkage map and mapped trait quantitative trait loci (QTL). We found genetic trade-offs between leaf size and growth rate FVT and uncovered differences in genotypic and QTL correlations involving FVT vs STPs. We identified leaf shape (allometry) as a genetic module independent of length and width and identified selection on FVT parameters of development. Leaf shape is associated with venation features that affect desiccation resistance. The genetic independence of leaf shape from other leaf traits may therefore enable crop optimization in leaf shape without negative effects on traits such as size, growth rate, duration or gas exchange.

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Source
http://dx.doi.org/10.1111/nph.13509DOI Listing

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