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Originally published as Genetics Published Articles Ahead of Print on January 31, 2005.
Genetics, Vol. 169, 2295-2303, April 2005, Copyright © 2005
doi:10.1534/genetics.104.039198
Genetic Architecture of Transcript-Level Variation in Differentiating Xylem of a Eucalyptus Hybrid
Matias Kirst*,
,1,
Christopher J. Basten
,
Alexander A. Myburg
,
Zhao-Bang Zeng and
Ronald R. Sederoff*
* Forest Biotechnology Group, North Carolina State University, Raleigh, North Carolina 27695
Functional Genomics and Genetics Graduate Program, North Carolina State University, Raleigh, North Carolina 27695
Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina 27695
Department of Genetics, Forestry and Agricultural Biotechnology Institute, University of Pretoria, Pretoria 0002, South Africa
1 Corresponding author: School of Forest Resources and Conservation, Newins-Ziegler Hall, Room 367, University of Florida, Gainesville, FL 32611
Species diversity may have evolved by differential regulation of a similar set of genes. To analyze and compare the genetic architecture of transcript regulation in different genetic backgrounds of Eucalyptus, microarrays were used to examine variation in mRNA abundance in the differentiating xylem of a E. grandis pseudobackcross population [E. grandis x F1 hybrid (E. grandis x E. globulus)]. Least-squares mean estimates of transcript levels were generated for 2608 genes in 91 interspecific backcross progeny. The quantitative measurements of variation in transcript abundance for specific genes were mapped as expression QTL (eQTL) in two single-tree genetic linkage maps (F1 hybrid paternal and E. grandis maternal). EQTL were identified for 1067 genes in the two maps, of which 811 were located in the F1 hybrid paternal map, and 451 in the E. grandis maternal map. EQTL for 195 genes mapped to both parental maps, the majority of which localized to nonhomologous linkage groups, suggesting trans-regulation by different loci in the two genetic backgrounds. For 821 genes, a single eQTL that explained up to 70% of the transcript-level variation was identified. Hotspots with colocalized eQTL were identified in both maps and typically contained genes associated with specific metabolic and regulatory pathways, suggesting coordinated genetic regulation.
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