Identification of the Submergence Tolerance QTL <i>Come Quick Drowning1 (CQD1)</i> in <i>Arabidopsis thaliana</i>

Global climate change is predicted to increase water precipitation fluctuations and lead to localized prolonged floods in agricultural fields and natural plant communities. Thus, understanding the genetic basis of submergence tolerance is crucial in order to improve plant survival under these conditions. In this study, we performed a quantitative trait locus (QTL) analysis in Arabidopsis to identify novel candidate genes for increased submergence tolerance by using Kas-1 and Col (gl1) parental accessions and their derived recombinant inbred lines (RILs). We measured survival after submergence in dark for a 13-day period and used median lethal time, LT50 values for the QTL analysis. A major QTL, the Come Quick, Drowning (CQD1) locus, was detected in 2 independent experiments on the lower arm of chromosome 5 involved in higher submergence tolerance in the parental accession Kas-1. For fine-mapping, we then constructed near isogenic lines (NILs) by backcrossing the CQD1 QTL region. We also analyzed QTL regions related to size, leaf number, flowering, or survival in darkness and none of the QTL related to these traits overlapped with CQD1. The submergence tolerance QTL, CQD1, region detected in this study includes genes that have potential to be novel candidates effecting submergence tolerance such as trehalose-6-phosphate phosphatase and respiratory burst oxidase protein D. Gene expression and functional analysis for these genes under submergence would reveal the significance of these novel candidates and provide new perspectives for understanding genetic basis of submergence tolerance

О некоторых тенденциях, осложнивших в начале ХХI века перспективы курортно-рекреационного развития Крыма

Целью работы явился анализ взаимовлияния различных факторов, сужающих потенциал туристско-рекреационной привлекательности Крыма, для уточнения возможностей объективного прогнозирования его перспективного развития

Genomic regions in crop-wild hybrids of Lettuce are affected differrently in different environments: implications for crop breeding

Many crops contain domestication genes that are generally considered to lower fitness of crop–wild hybrids in the wild environment. Transgenes placed in close linkage with such genes would be less likely to spread into a wild population. Therefore, for environmental risk assessment of GM crops, it is important to know whether genomic regions with such genes exist, and how they affect fitness. We performed quantitative trait loci (QTL) analyses on fitness(-related) traits in two different field environments employing recombinant inbred lines from a cross between cultivated Lactuca sativa and its wild relative Lactuca serriola. We identified a region on linkage group 5 where the crop allele consistently conferred a selective advantage (increasing fitness to 212% and 214%), whereas on linkage group 7, a region conferred a selective disadvantage (reducing fitness to 26% and 5%), mainly through delaying flowering. The probability for a putative transgene spreading would therefore depend strongly on the insertion location. Comparison of these field results with greenhouse data from a previous study using the same lines showed considerable differences in QTL patterns. This indicates that care should be taken when extrapolating experiments from the greenhouse, and that the impact of domestication genes has to be assessed under field conditions

Genomic and environmental selection patterns in two distinct lettuce crop-wild hybrid crosses

Genomic selection patterns and hybrid performance influence the chance that crop (trans)genes can spread to wild relatives. We measured fitness(-related) traits in two different field environments employing two different crop–wild crosses of lettuce. We performed quantitative trait loci (QTL) analyses and estimated the fitness distribution of early- and late-generation hybrids. We detected consistent results across field sites and crosses for a fitness QTL at linkage group 7, where a selective advantage was conferred by the wild allele. Two fitness QTL were detected on linkage group 5 and 6, which were unique to one of the crop–wild crosses. Average hybrid fitness was lower than the fitness of the wild parent, but several hybrid lineages outperformed the wild parent, especially in a novel habitat for the wild type. In early-generation hybrids, this may partly be due to heterosis effects, whereas in late-generation hybrids transgressive segregation played a major role. The study of genomic selection patterns can identify crop genomic regions under negative selection across multiple environments and cultivar–wild crosses that might be applicable in transgene mitigation strategies. At the same time, results were cultivar-specific, so that a case-by-case environmental risk assessment is still necessary, decreasing its general applicability

Abiotic stress QTLs in lettuce crop–wild hybrids: comparing greenhouse and field experiments

The development of stress-tolerant crops is an increasingly important goal of current crop breeding. A higher abiotic stress tolerance could increase the probability of introgression of genes from crops to wild relatives. This is particularly relevant to the discussion on the risks of new GM crops that may be engineered to increase abiotic stress resistance. We investigated abiotic stress QTL in greenhouse and field experiments in which we subjected recombinant inbred lines from a cross between cultivated Lactuca sativa cv. Salinas and its wild relative L. serriola to drought, low nutrients, salt stress, and aboveground competition. Aboveground biomass at the end of the rosette stage was used as a proxy for the performance of plants under a particular stress. We detected a mosaic of abiotic stress QTL over the entire genome with little overlap between QTL from different stresses. The two QTL clusters that were identified reflected general growth rather than specific stress responses and colocated with clusters found in earlier studies for leaf shape and flowering time. Genetic correlations across treatments were often higher among different stress treatments within the same experiment (greenhouse or field), than among the same type of stress applied in different experiments. Moreover, the effects of the field stress treatments were more correlated with those of the greenhouse competition treatments than to those of the other greenhouse stress experiments, suggesting that competition rather than abiotic stress is a major factor in the field. In conclusion, the introgression risk of stress tolerance (trans-)genes under field conditions cannot easily be predicted based on genomic background selection patterns from controlled QTL experiments in greenhouses, especially field data will be needed to assess potential (negative) ecological effects of introgression of these transgenes into wild relatives

Elasticities and the link between demographic and evolutionary dynamics

Multivariate selection models and demographic matrix projections are closely related. The subtle differences among the parameters of both approaches (sensitivities, elasticities, selection differentials, and gradients) can be confusing. I suggest a hierarchical framework for analysis using elasticity path diagrams, "elastograms." The framework combines selection analysis fur the links between phenotypic traits (morphology, behavior) and fitness components (vital rates) with matrix analysis for the relationship between fitness components and population growth rate/fitness. Elasticities are often used to quantify the impact of a transition rate in the projection matrix on the population growth rate (lambda). Elasticities fur underlying fitness components such as fecundity and survival rates can be derived from their connection with the transition matrix entries. Yet other traits may affect lambda due to a functional relationship with one or more components of fitness: for instance, the timing of flowering of a plant may affect its seed yield. Elasticities can also be used to quantity the effects of such traits: they can be interpreted as selection gradients for traits expressed on a proportional (mean- standardized) scale. "Evolvabilities" (additive genetic variation in mean-standardized traits), rather than the heritabilities of traits, are needed to predict expected selection responses from the elasticities. Elasticities quantify the direct effect of a focal trait on lambda. integrated elasticities measure the impact of a trait through both its direct and indirect effects. This requires knowledge of the correlations among traits. Matrix projections and selection analysis (through multiple regression or path analysis) can be merged into an elasticity path diagram that summarizes the hierarchical relationships among traits and fitness. Such diagrams facilitate the identification of those traits that have the highest impact on the life cycle of the study organism and can be a tool to define the targets of management practices, as well as an aid in comparative life history research. [KEYWORDS: demography; elasticities; elasticity path diagrams;life history traits; path analysis; quantitative genetics; selection; selection; selection gradients Population-growth rate; finding confidence-limits; natural-selection; path-analysis; quantitative traits; projection matrices; sexual selection; life-histories; fitness; models