Understanding the response of a crop to water deficiency is the first step towards breeding drought-tolerant varieties. In this study, inbred maize (Zea mays L.) lines KS140 and KS141 were subjected to drought stress by withholding water for 10 days at the V5 or V6 leaf stage. Water-deficient plants experienced a decrease in relative leaf water content, stomatal conductance, net CO2 assimilation rate, and water use efficiency compared to well-watered plants. This was accompanied by a decrease in the relative leaf water content that resulted in severe growth retardation in KS140 and KS141. However, leaf chlorophyll content in KS140 was unchanged. To understand the proteome dynamics during the 10-day drought stress in maize leaves, comparative proteome analysis was carried out between the well-watered and water-withheld leaves. Differential expression was observed for 29 protein spots from KS140 and 14 protein spots from KS141, and these were identified using MALDI-TOF mass spectrometry. Among identified proteins, metabolism and stress related proteins were highly were increased by drought stress. This study provides a protein profile of a Korean maize inbred line during drought stress, which will be valuable for future studies of the molecular mechanisms underlying drought resistance and for development of selective breeding markers for drought tolerance in maize.

The groundnut or cultivated peanut (Arachis hypogaea L.) in Korea consists of 36 domestic varieties which have been developed and registered as cultivars for the public during last 25 years. To screen and identify of Korean peanut varieties and genetic resources, we present a simple and reliable method. A methodology based on simple sequence repeat (SSR) markers developed and widely used for prominent gene identification and variety discrimination. For identification of those 36 Korean peanut varieties, 238 unique peanut SSR markers were selected from some previously reported results, synthesized and used for polymerase chain reaction (PCR). Data were taken through acryl amide gel electrophoresis and changed into proper formats for application of data mining analysis using Biomine (all-in-one functional genomics data mining program). Consequently, twelve SSR primers were investigated and revealed the differences between those 36 varieties. These primer pairs amplified 27 alleles with an average of 2.3 allele per primer pair. In addition, those results showed genetic relationship by classification method within 36 varieties. The approach described here could be applied to monitoring of our varieties and adapting to peanut breeding program.