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

被引:0
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作者
M. M. Sewell
M. F. Davis
G. A. Tuskan
N. C. Wheeler
C. C. Elam
D. L. Bassoni
D. B. Neale
机构
[1] Environmental Sciences Division,
[2] Oak Ridge National Laboratory,undefined
[3] P.O. Box 2088,undefined
[4] MS-6422,undefined
[5] Bldg 1059,undefined
[6] Rm 103,undefined
[7] Oak Ridge,undefined
[8] TN 37831-2008,undefined
[9] USA,undefined
[10] National Renewable Energy Laboratory,undefined
[11] 1617 Cole Boulevard,undefined
[12] Golden,undefined
[13] CO 80401,undefined
[14] USA,undefined
[15] George Staebler Research Center,undefined
[16] Weyerhaeuser Company,undefined
[17] PO Box 420,undefined
[18] Centralia,undefined
[19] WA 98531,undefined
[20] USA,undefined
[21] Institute of Forest Genetics,undefined
[22] USDA Forest Service,undefined
[23] Department of Environmental Horticulture,undefined
[24] University of California,undefined
[25] One Shields Avenue,undefined
[26] Davis,undefined
[27] CA 95616,undefined
[28] USA,undefined
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关键词
Keywords Pinus taeda L.; QTL mapping; Wood chemistry; α-Cellulose; Hemicellulose; Lignin;
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摘要
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, α-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., α-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 QTL×environment 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.
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页码:214 / 222
页数:8
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