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BMC Genomics  2012 

Expression variation in connected recombinant populations of Arabidopsis thaliana highlights distinct transcriptome architectures

DOI: 10.1186/1471-2164-13-117

Keywords: eQTL, Natural variation, Selection, RILs

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Abstract:

The utilisation of the novel R/eqtl package (which goal is to automatize and extend functions from the R/qtl package) allowed us to map 4,290 and 6,534 eQTLs in the Cvi-0 × Col-0 and Bur-0 × Col-0 recombinant populations respectively. In agreement with previous studies, we observed a larger phenotypic variance explained by eQTLs in linkage with the controlled gene (potentially cis-acting), compared to distant loci (acting necessarily indirectly or in trans). Distant eQTLs hotspots were essentially not conserved between crosses, but instead, cross-specific. Accounting for confounding factors using a probabilistic approach (VBQTL) increased the mapping resolution and the number of significant associations. Moreover, using local eQTLs obtained from this approach, we detected evidence for a directional allelic effect in genes with related function, where significantly more eQTLs than expected by chance were up-regulated from one of the accessions. Primary experimental data, analysis parameters, eQTL results and visualisation of LOD score curves presented here are stored and accessible through the QTLstore service database http://qtlstore.versailles.inra.fr/ webcite.Our results demonstrate the extensive diversity and moderately conserved eQTL landscape between crosses and validate the utilisation of expression traits to explore for candidates behind phenotypic variation among accessions. Furthermore, this stresses the need for a wider spectrum of diversity to fully understand expression trait variation within a species.Most traits vary quantitatively between individuals and are significantly influenced by genetic variation and its interaction with the environment. In general, transcript abundance of a gene can be considered as a quantitative trait since it differs between individuals with respect to genetic factors [1,2]. The utilisation of technologies such as microarray and, lately, next generation sequencing, allowed the simultaneous quantification of thousands of tra

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