Literature DB >> 12582689

Identification of QTLs influencing wood property traits in loblolly pine ( Pinus taeda L.). II. Chemical wood properties.

M. M. Sewell1, M. F. Davis, G. A. Tuskan, N. C. Wheeler, C. C. Elam, D. L. Bassoni, D. B. Neale.   

Abstract

Chemical wood property traits were analyzed for the presence of quantitative trait loci (QTLs) in a three-generation outbred pedigree of loblolly pine ( Pinus taeda L.). These traits were assayed using pyrolysis molecular beam mass spectrometry and include mass spectrum peak intensities associated with carbohydrates, alpha-cellulose and hemicellulose sugars, and lignin. Models for projection to latent structures (PLS) were used to also estimate the chemical composition of cell walls (i.e., alpha-cellulose, galactan and lignin) from mass spectrum data using multivariate regression. Both earlywood and latewood fractions from the fifth annual ring were analyzed for each trait. An interval mapping approach designed for an outbred pedigree was used to estimate the number of QTLs, the magnitude of QTL effects, and their genomic position. Eight unique QTLs influencing cell wall chemistry were detected from multiple peak intensities and/or PLS estimates using the one- and two-QTL models. Significant differences in chemical contents were observed among the populations from North Carolina vs Oklahoma, and results from QTLxenvironment analyses suggest that QTLs interact with environmental location. QTLs should be verified in larger experiments and in different genetic and environmental backgrounds. QTL mapping will help towards eventually identifying genes having a major effect on chemical wood properties.

Entities:  

Year:  2002        PMID: 12582689     DOI: 10.1007/s001220100697

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.699


  27 in total

1.  Association genetics in Pinus taeda L. I. Wood property traits.

Authors:  Santiago C González-Martínez; Nicholas C Wheeler; Elhan Ersoz; C Dana Nelson; David B Neale
Journal:  Genetics       Date:  2006-11-16       Impact factor: 4.562

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4.  Targeted linkage map densification to improve cell wall related QTL detection and interpretation in maize.

Authors:  Audrey Courtial; Justine Thomas; Matthieu Reymond; Valérie Méchin; Jacqueline Grima-Pettenati; Yves Barrière
Journal:  Theor Appl Genet       Date:  2013-01-30       Impact factor: 5.699

5.  Transcript abundance patterns of Populus C-repeat binding factor2 orthologs and genetic association of PsCBF2 allelic variation with physiological and biochemical traits in response to abiotic stress.

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Journal:  Planta       Date:  2015-04-28       Impact factor: 4.116

6.  Near-saturated and complete genetic linkage map of black spruce (Picea mariana).

Authors:  Bum-Yong Kang; Ishminder K Mann; John E Major; Om P Rajora
Journal:  BMC Genomics       Date:  2010-09-24       Impact factor: 3.969

7.  Genetic mapping in (Populus tomentosa x Populus bolleana) and P. tomentosa Carr. using AFLP markers.

Authors:  D Zhang; Z Zhang; K Yang; B Li
Journal:  Theor Appl Genet       Date:  2003-10-16       Impact factor: 5.699

8.  Identification of quantitative trait loci influencing wood property traits in loblolly pine (Pinus taeda L.). III. QTL Verification and candidate gene mapping.

Authors:  Garth R Brown; Daniel L Bassoni; Geoffrey P Gill; Joseph R Fontana; Nicholas C Wheeler; Robert A Megraw; Mark F Davis; Mitchell M Sewell; Gerald A Tuskan; David B Neale
Journal:  Genetics       Date:  2003-08       Impact factor: 4.562

9.  Comparative mapping in the Pinaceae.

Authors:  Konstantin V Krutovsky; Michela Troggio; Garth R Brown; Kathleen D Jermstad; David B Neale
Journal:  Genetics       Date:  2004-09       Impact factor: 4.562

10.  A RAPD, AFLP and SSR linkage map, and QTL analysis in European beech (Fagus sylvatica L.).

Authors:  M Scalfi; M Troggio; P Piovani; S Leonardi; G Magnaschi; G G Vendramin; P Menozzi
Journal:  Theor Appl Genet       Date:  2003-10-22       Impact factor: 5.699

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