High-latitude ion transport and energetic explorer (HI-LITE): a mission to investigate ion outflow from the high-latitude ionosphere

The proposed HI-LITE Explorer will investigate the global ion outflow from the high-latitude ionosphere, its relationship to auroral features, and the consequences of this outflow on magnetospheric processes. The unique nature of the HI-LITE Explorer images will allow temporal and spatial features of the global ion outflow to be determined. The mission's scientific motivation comes from the fundamental role high-latitude ionospheric ions play in the dynamics of the solar wind driven magnetospheric-ionospheric system. These outflows are a major source of plasma for the magnetosphere and it is believed they play an important role in the triggering of substorms. In addition this paper describes the HI-LITE spacecraft and instruments.

Genetic dissection of heterosis using epistatic association mapping in a partial NCII mating design

Heterosis refers to the phenomenon in which an F1 hybrid exhibits enhanced growth or agronomic performance. However, previous theoretical studies on heterosis have been based on bi-parental segregating populations instead of F1 hybrids. To understand the genetic basis of heterosis, here we used a subset of F1 hybrids, named a partial North Carolina II design, to perform association mapping for dependent variables: original trait value, general combining ability (GCA), specific combining ability (SCA) and mid-parental heterosis (MPH). Our models jointly fitted all the additive, dominance and epistatic effects. The analyses resulted in several important findings: 1) Main components are additive and additive-by-additive effects for GCA and dominance-related effects for SCA and MPH, and additive-by-dominant effect for MPH was partly identified as additive effect; 2) the ranking of factors affecting heterosis was dominance > dominance-by-dominance > over-dominance > complete dominance; and 3) increasing the proportion of F1 hybrids in the population could significantly increase the power to detect dominance-related effects, and slightly reduce the power to detect additive and additive-by-additive effects. Analyses of cotton and rapeseed datasets showed that more additive-by-additive QTL were detected from GCA than from trait phenotype, and fewer QTL were from MPH than from other dependent variables.