Natural variability offers a large resource of polymorphism, which is often explored to identify traits with environmental adaptive value or quality properties. Responses to environmental conditions depend on numerous genes and are typically controlled by QTLs. Genomic mapping of such QTLs may lead to the identification and cloning of important regulatory genes or allelic variants. It could also provide genetic markers for molecular breeding and/or cloned genes for genetic engineering for the improvement of stress tolerance in plants (Papdi et al. 2009).
Natural variability is often based on minor genetic changes, generating small quantitative alterations in responses to environmental conditions. One single nucleotide change, so-called single nucleotide polymorphism (SNP), could lead to different plant yield (Fleury et al. 2010; Papdi et al. 2009; Rafalski 2002; Xing and Zhang 2010).
The identification of genetic variability which affects stress responses requires phenotypic screenings capable of distinguishing between plants with different stress tolerance. Although previously tedious and time-consuming, next-generation sequencing of natural accessions can reveal sequence variability at the genome scale and will facilitate the large-scale identification of SNPs in different ecotypes and varieties. This is one of the goals of the "1001 Genomes Project," spearheaded by Magnus Nordborg, Joe Ecker,
Fig. 4.5 Proposed points of genetic engineering for obtaining plants with improved K+ nutrition: Upregulation of known root K+ uptake transporters (HAK5) and channels (AKT1); selective upregulation of Na+/K+ transporters (HKT); upregulation of unknown K+ transporters (CPAs, CNGCs). In addition, protein activity and selectivity may be also modified to enhance K+ uptake
Fig. 4.5 Proposed points of genetic engineering for obtaining plants with improved K+ nutrition: Upregulation of known root K+ uptake transporters (HAK5) and channels (AKT1); selective upregulation of Na+/K+ transporters (HKT); upregulation of unknown K+ transporters (CPAs, CNGCs). In addition, protein activity and selectivity may be also modified to enhance K+ uptake and Detlef Weigel among others, http:// 1001genomes.org/where 617 accessions have been committed as of 2010-6-2.
There are many examples of successful uses of genetic markers and QTL mapping. ERECTA was the first Arabidopsis gene that was mapped as a main QTL, and it regulates transpiration efficiency by controlling leaf photosynthesis efficiency and stomatal conductance (Masle et al. 2005) . Freezing tolerance is controlled by seven QTLs in Arabidopsis. QTL mapping revealed that the C-repeat binding factor (CBF) locus is the most important component in cold acclimation (Alonso-Blanco et al. 2005).
As mentioned above, the identification of QTLs for determining salt tolerance or K+ accumulation have highlighted the importance of HKT transporters in these processes. High-throughput ionomic coupled with genomic analysis allowed the identification of the genetic alteration that drives the natural variation in shoot Na+ accumulation in Arabidopsis populations (Rus et al. 2006). Polymorphism of the AtHKTl gene and sensitive wild populations of Arabidopsis illustrate the importance of this transporter in salt tolerance. Other examples are the already mentioned SKC1, a rice HKT-type Na+-selective transporter involved in unloading Na+ from the xylem, characterized as a QTL for salt tolerance (Ren 2005); or the durum wheat Nax1 and Nax2 loci, linked to Na+ exclusion which correspond to the Na+ transporters HKT1;4 (HKT7) and
HKT1;5 (HKT8), respectively (Byrt et al. 2007; Huang et al. 2006). Recently, RAS1 (Response to ABA and Salt 1) were found by using QTL mapping of a recombinant inbred population derived from Landsberg erecta (Ler; salt and ABA sensitive) x Shakdara (Sha; salt and ABA resistant). This transcription factor have been shown to play an important role in salt tolerance and ABA sensitivity (Ren et al. 2010).
As we can see, the analysis of natural variation in crop plants and Arabidopsis has provided an unprecedented amount of information on the genetic and molecular mechanisms that determine intraspecific variation and adaptation. It can be anticipated that this trend will continue in the next decade, especially with the broad implementation of "-omics" technologies for the precise analysis of natural variation at different levels (Alonso-Blanco et al. 2009).
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