Quantitative traits, such as size and weight in animals and seed yield in plants, are distributed normally, even within a population of genetically identical individuals. For example, in plants, various factors, such as local soil quality, microclimate, and sowing depth, affect growth differences among individual plants of isogenic populations. Besides these physical factors, also epigenetic components contribute to differences in growth and yield. The network that regulates crop yield is still not well understood. Although this network is expected to have epigenetic elements, it is completely unclear whether it would be possible to shape the epigenome to increase crop yield. Here we show that energy use efficiency is an important factor in determining seed yield in canola (Brassica napus) and that it can be selected artificially through an epigenetic feature. From an isogenic canola population of which the individual plants and their self-fertilized progenies were recursively selected for respiration intensity, populations with distinct physiological and agronomical characteristics could be generated. These populations were found to be genetically identical, but epigenetically different. Furthermore, both the DNA methylation patterns as well as the agronomical and physiological characteristics of the selected lines were heritable. Hybrids derived from parent lines selected for high energy use efficiencies had a 5% yield increase on top of heterosis. Our results demonstrate that artificial selection allows the increase of the yield potential by selecting populations with particular epigenomic states. Brassica napus ͉ epigenome

The aim of this paper is to establish a test method for the screening of bioengineered cotton fibers with an improved reactivity through the incorporation of positively charged nitrogen moieties. For this purpose a spectrophotometric method based on the absorption of a negatively charged dye (Acid Orange 7) is extensively studied. The processing parameters have been optimized for analyzing small amounts of fibers and the feasibility of the method is examined by using two other well established techniques for nitrogen analysis. Good correlations were obtained between the different methods, however, the reproducibility of the Acid Orange 7 was superior to the other two methods. Moreover, statistically significant differences were found between fibers from cotton lines designed to produce oligochitin and control fibers without oligochitin. This shows that the proposed method is capable of accurately detecting increased nitrogen levels in bioengineered cotton fibers