QTL mapping experiments provide heterogeneous results due to the use of different genotypes, environments, and sampling variation. Compilation of QTL mapping results yields a more complete picture of the genetic control of a trait than can be obtained in any single study, and reveals the genomic organization of trait variation. In an early investigation, QTL for domestication traits in independently-domesticated cereal lineages fell into corresponding intervals of the respective genomes more often than could be explained by chance (Paterson et al. 1995). Likewise, non-random correspondence of QTLs associated with domestication traits (e.g. fruit quality, weight and shape) is also found among tomato, pepper, and eggplant (Gephardt et al. 1991; Tanksley et al. 1992; Frary et al. 2000, 2003; Thorup et al. 2000; Doganlar et al. 2002a; Van der and Tanksley 2003).
The flowering time is conferred by numerous QTLs in maize (Chardon et al. 2004), and its molecular basis appears to be correlated across the maize-sorghum-rice lineages (Lin et al. 1995; Salvi et al. 2007) Similarly, conserved QTLs confer 'timing of bud burst' in oak and chestnut tree species (Casasoli et al. 2006) and this conservation may aid in the identification of these genomic regions. Non-conserved QTLs may have roles in local adaptation and species differentiation (Casasoli et al. 2006). A particularly extensive meta-analysis of 432 QTLs mapped in one diploid and ten tetraploid cotton populations revealed the sub genomic distributions of QTLs, identified hotspots for QTLs affecting particular traits, and showed that single-gene mutants in fiber characteristics may profoundly alter the QTL landscape, suggesting that fiber-related traits may be controlled by a complex gene network (Rong et al. 2007).
It is important to emphasize that non-random correspondence of QTL position does not necessarily mean that same genes confer the QTLs. For example, QTLs associated with the tb1 gene conferring branching in maize, are conserved across the Poaceae family, but have a very meager role in foxtail millet (Doust et al. 2004). Such non-random QTL distributions could reflect non-random distributions of particular gene functional groups (i.e. gene clusters).
In isolating genes responsible for QTLs, microcollinearity aids in designing new markers from well-studied plant species to be applied to more complex genomes or orphan crops. For instance, two wheat QTLs associating with vernalization genes (VRN1 and VRN2) (Dubcovsky et al. 1998; Tranquilli and Dubcovsky 2000) were cloned in part by designing additional markers based on the rice and sorghum genomes. Rice is syntenic to many corresponding regions containing genes involved in different developmental processes such as tassel and ear development in maize, and has been utilized for cloning these genes. Likewise, sorghum is closely related to major cellulosic biofuels crops including Saccharum (sugarcane) and Miscanthus, and its sequence is expected to accelerate progress in improvement of biofuels crops. Conservation of gene order between rice and barley genomes was not found in regions containing disease resistance (Bortiri et al. 2006). However, two of the three QTLs associated with clubroot resistance in B. rapa are syntenic to a disease resistance gene cluster, also termed as major recognition complexes (MRCs, Speulman et al. 1998) on chromosome 4 of Arabidopsis suggesting a possible common origin of MRCs from an ancestral genome (Suwabe et al. 2006).
Comparison of multiple QTL mapping studies is not only advantageous in molecular breeding experiments but also has increased utility in cloning of the genomic regions. A total of 432 QTLs conferring different traits in 11 cotton populations were aligned and projected on a reference map which fosters deducing synteny between the cotton and Arabidopsis genomes, revealing non-random distribution of fiber and trichome-related genes in the two genomes (Rong et al. 2007). This correspondence suggests that the identification of genes for trichome development in Arabidopsis may lead indirectly to the identification of fiber-related genes in cotton.
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