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Genetic dissection of growth, wood basic density and gene expression in interspecific backcrosses of Eucalyptus grandis and E. urophylla

Overview of attention for article published in BMC Genomic Data, July 2012
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Title
Genetic dissection of growth, wood basic density and gene expression in interspecific backcrosses of Eucalyptus grandis and E. urophylla
Published in
BMC Genomic Data, July 2012
DOI 10.1186/1471-2156-13-60
Pubmed ID
Authors

Anand Raj Kumar Kullan, Maria M van Dyk, Charles A Hefer, Nicoletta Jones, Arnulf Kanzler, Alexander A Myburg

Abstract

F1 hybrid clones of Eucalyptus grandis and E. urophylla are widely grown for pulp and paper production in tropical and subtropical regions. Volume growth and wood quality are priority objectives in Eucalyptus tree improvement. The molecular basis of quantitative variation and trait expression in eucalypt hybrids, however, remains largely unknown. The recent availability of a draft genome sequence (http://www.phytozome.net) and genome-wide genotyping platforms, combined with high levels of genetic variation and high linkage disequilibrium in hybrid crosses, greatly facilitate the detection of quantitative trait loci (QTLs) as well as underlying candidate genes for growth and wood property traits. In this study, we used Diversity Arrays Technology markers to assess the genetic architecture of volume growth (diameter at breast height, DBH) and wood basic density in four-year-old progeny of an interspecific backcross pedigree of E. grandis and E. urophylla. In addition, we used Illumina RNA-Seq expression profiling in the E. urophylla backcross family to identify cis- and trans-acting polymorphisms (eQTLs) affecting transcript abundance of genes underlying QTLs for wood basic density.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 84 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 1%
Norway 1 1%
South Africa 1 1%
Unknown 81 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 18%
Student > Master 12 14%
Student > Ph. D. Student 10 12%
Student > Doctoral Student 10 12%
Professor > Associate Professor 8 10%
Other 22 26%
Unknown 7 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 52 62%
Biochemistry, Genetics and Molecular Biology 7 8%
Environmental Science 4 5%
Computer Science 2 2%
Unspecified 2 2%
Other 8 10%
Unknown 9 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 July 2012.
All research outputs
#22,759,452
of 25,374,647 outputs
Outputs from BMC Genomic Data
#1,008
of 1,204 outputs
Outputs of similar age
#160,516
of 177,940 outputs
Outputs of similar age from BMC Genomic Data
#16
of 17 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,204 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.