Phenotyping shows improved physiological traits and seed yield of transgenic wheat plants expressing the alfalfa aldose reductase under permanent drought stress

Members of the aldo-keto reductase family including aldose reductases are involved in antioxidant defense by metabolizing a wide range of lipid peroxidation-derived cytotoxic compounds. Therefore, we produced transgenic wheat genotypes over-expressing the cDNA of alfalfa aldose reductase gene. These plants consequently exhibit 1.5-4.3 times higher detoxification activity for the aldehyde substrate. Permanent drought stress was generated in the greenhouse by growing wheat plants in soil with 20 % water capacity. The control and stressed plants were monitored by a semi automatic phenotyping platform providing computer-controlled watering, digital and thermal imaging. Calculation of biomass values was based on the correlation (R2 = 0.7556) between fresh weight and green pixel-based shoot surface area. The green biomass production by plants of the three transgenic lines was 12-26-41 % higher than the non-transgenic plants' grown under water limitation. Thermal imaging of stressed non-transgenic plants indicated an elevation in the leaf temperature. The thermal status of transformants was similar at both normal and suboptimal water regime. In drought, the transgenic plants used more water during the growing season. The described phenotyping platform provided a comprehensive data set demonstrating the improved physiological condition of the drought stressed transgenic wheat plants in the vegetative growth phase. In soil with reduced water capacity two transgenic genotypes showed higher seed weight per plant than the control non-transgenic one. Limitation of greenhouse-based phenotyping in analysis of yield potential is discussed. © 2013 The Author(s)

Classification of the Y-haplogroup distributions of Western Eurasian populations using a self-learning algorithm

The understanding of historical relationship between populations is a core aspect of human population history studies. We have compared the frequency of 18 different Y-SNP haplogroups in 90 Western Eurasian populations. Classification of haplogroup distribution vectors using a new self-learning classification algorithm so called ‘‘self-organizing cloud (SOC)’’ proved to be an effective tool to identify population groups, which share common paternal genetic features. By means of the algorithm, we have determined 10 different classes of populations based on the similarity of haplogroup composition. The analysis showed that paternal genetic markers tend to reflect geographical proximity of populations better than linguistic relationship, although certain Y-SNP haplogroups have relatively good correlation with specific language families. These observations are based on the comparative analysis of the Hg distributions of contemporary populations may reflect demographic history of them in the past

New clustering methods for population comparison on paternal lineages

The goal of this study is to show two new clustering and visualising techniques developed to find the most typical clusters of 18-dimensional Y chromosomal haplogroup frequency distributions of 90 Western Eurasian populations. The first technique called “self-organizing cloud (SOC)” is a vector-based self-learning method derived from the Self Organising Map and non-metric Multidimensional Scaling algorithms. The second technique is a new probabilistic method called the “maximal relation probability” (MRP) algorithm, based on a probability function having its local maximal values just in the condensation centres of the input data. This function is calculated immediately from the distance matrix of the data and can be interpreted as the probability that a given element of the database has a real genetic relation with at least one of the remaining elements. We tested these two new methods by comparing their results to both each other and the k-medoids algorithm. By means of these new algorithms, we determined 10 clusters of populations based on the similarity of haplogroup composition. The results obtained represented a genetically, geographically and historically well-interpretable picture of 10 genetic clusters of populations mirroring the early spread of populations from the Fertile Crescent to the Caucasus, Central Asia, Arabia and Southeast Europe. The results show that a parallel clustering of populations using SOC and MRP methods can be an efficient tool for studying the demographic history of populations sharing common genetic footprints

CMS : the TriDAS Project Technical Design Report; v.1, the Trigger Systems

CM