Song Wu¹, Jie Yang¹, Youjun Huang², Yao Li³, Tongming Yin⁴, Stan D. Wullschleger⁴, Gerald A. Tuskan⁴ and Rongling Wu^5,6,7

¹Department of Biostatistics, St. Jude Children’s Research Hospital, Memphis, TN, USA. ²School of Forestry and Biotechnology, Zhejiang Forestry University, Lin’an, Zhejiang, China. ³Department of Statistics, West Virginia University, Morgantown, WV, USA. ⁴Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA. ⁵Department of Public Health Sciences, Pennsylvania State College of Medicine, Hershey, PA, USA. ⁶Department of Statistics, Pennsylvania State University, University Park, PA, USA. ⁷Center for Computational Biology, College of Life Sciences and Biotechnology, Beijing Forestry University, Beijing, China.

Abstract

A pseudo-testcross pedigree is widely used for mapping quantitative trait loci (QTL) in outcrossing species, but the model for analyzing pseudo-testcross data borrowed from the inbred backcross design can only detect those QTLs that are heterozygous only in one parent. In this study, an intercross model that incorporates the high heterozygosity and phase uncertainty of outcrossing species was used to reanalyze a published data set on QTL mapping in poplar trees. Several intercross QTLs that are heterozygous in both parents were detected, which are responsible not only for biomass traits, but also for their genetic correlations. This study provides a more complete identification of QTLs responsible for economically important biomass traits in poplars.